CN102800120B - Emergency disaster situation display system and method based on multiple intelligent bodies - Google Patents
Emergency disaster situation display system and method based on multiple intelligent bodies Download PDFInfo
- Publication number
- CN102800120B CN102800120B CN201210202747.6A CN201210202747A CN102800120B CN 102800120 B CN102800120 B CN 102800120B CN 201210202747 A CN201210202747 A CN 201210202747A CN 102800120 B CN102800120 B CN 102800120B
- Authority
- CN
- China
- Prior art keywords
- agent
- data
- node
- atural object
- collection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Abstract
The invention discloses an emergency disaster situation display system and an emergency disaster situation display method based on multiple intelligent bodies, which can obtain disaster information in real time and can realize dynamic and multi-granularity three-dimensional display. The method comprises the following steps of: utilizing an SSHC (Scale Space Hierarchical Clustering) algorithm to process a remote sensing image to establish a hierarchical clustering tree; taking each node in the hierarchical clustering tree as a class; setting a surface feature corresponding to each class and establishing a three-dimensional model of each class; when a disaster situation is displayed, receiving a user instruction, wherein the user instruction comprises an expectedly-displayed surface feature A appointed by a user, and finding the expectedly-displayed surface feature A in the hierarchical clustering tree to be taken as a sub-tree of a tree root; creating collection intelligent bodies to collect data of bottom layer nodes in the sub-tree; creating organization intelligent bodies to collect data of other grades of the nodes except the bottom layer nodes from the collection intelligent bodies or the other organization intelligent bodies; rendering each type of the three-dimensional model according to the data of each node to form a three-dimensional geographic pattern of the surface feature A and displaying the three-dimensional geographic pattern; and displaying the three-dimensional geographic pattern with thinner granularity in the surface feature A.
Description
Technical field
The invention belongs to three-dimensional situation and show field, relate to a kind of emergent the condition of a disaster situation display packing and system thereof based on multiple agent.
Background technology
Calamity emergency refers on the basis of disaster knowledge, utilizes database technology, geographic information system technology, according to causality analysis and decision-making corresponding relation, sets up the process from the dynamic demonstration of disaster, Hazard Assessment to final formulation emergency preplan.For effectively protecting people life property safety, reducing economic loss, China starts progressively to carry out the emergency system research towards disaster as far back as early 1990s.Along with the development of space technology, infotech, virtual reality technology is that calamity emergency system has been brought new development trend: the one, the use of various monitor satellites and unmanned plane, real-time, continuous, stable observed image can be provided, can obtain the live state information of the condition of a disaster, thereby increased the time attribute of information, can make demonstration information is no longer static image or scene; The 2nd, the quoting of virtual reality technology, for the three-dimensional display system that realizes the displaying of structure to disaster view multi-angle, full-time sky provides technical foundation.These new trends make the three dimension system that builds Real time dynamic display disaster situation become possibility.But, current emergency system framework mostly is the form of " database+data show ", this framework can not be accomplished Real-time Obtaining disaster information, and dynamically shows, the variation that particularly shows the landform that caused by geologic hazard, landforms in geologic hazard field can't be carried out real-time renewal and show.
Summary of the invention
In view of this, the invention provides a kind of emergent the condition of a disaster situation display packing and system thereof based on multiple agent, can Real-time Obtaining disaster information, and 3-D display dynamic, many granularities.
For solving the problems of the technologies described above, the invention provides a kind of emergent the condition of a disaster situation display packing based on multiple agent Agent, comprising:
The 1st step: disaster to be shown region is obtained to remote sensing images, adopt metric space hierarchical cluster SSHC algorithm to set up multiple dimensioned disaggregated model;
Described process of establishing is: adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, regulating resolution is scale parameter, to the last converge to a cluster point, thereby form the hierarchical clustering tree with scale parameter convergence, i.e. multiple dimensioned disaggregated model;
The 2nd step: using the each node in hierarchical clustering tree as a classification, set the represented atural object of each classification; For each node setting identification, this mark unique identification node different classes of on the one hand, but also represent the membership between node;
The 3rd step: according to hierarchical clustering tree, set up three-dimensional model corresponding to each classification in each layer, and according to the geographic coordinate of the each three-dimensional model of atural object set positions in remote sensing images; This geographic coordinate for showing three-dimensional geographic pattern in the 8th step in image in conjunction with three-dimensional model;
The 4th step: when actual the condition of a disaster situation shows, receive user instruction, user instruction comprises the atural object A that hope that user specifies shows is searched the atural object A that shows taking the described hope subtree as tree root in hierarchical clustering tree;
The 5th step: the data acquisition based on Agent group:
Obtain the leaf node in described subtree; Set up one for each leaf node and gather Agent, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified; The data source that gathers Agent image data is the two class data that are temporary in data pool, and a class is from database, and another kind of is from outside real-time monitored data; Data in described database and described real-time monitored data are all to have stamped the data of mark;
The 6th step: the Organization of Data based on Agent group:
Set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes, according to mark, finds Agent corresponding to self child node, then gathers the data of all Agent that find, as its data;
The 7th step: according to the transformational relation setting in advance, be converted into by organizing Agent and gathering the data that in Agent, each Agent obtains the required information of three-dimensional model corresponding to node that shows this Agent representative;
The 8th step: the atural object A that the hope of specifying according to the 4th step user shows, in hierarchical clustering tree, find the corresponding node of this atural object A, the each three-dimensional model that utilizes the 7th step to determine shows required information, forms the three-dimensional geographic pattern of described atural object A and shows;
The 9th step: the atural object that the hope of specifying as user shows changes to the atural object B that in described subtree, a certain node is corresponding, without again carrying out data acquisition and tissue, the each three-dimensional model that directly utilizes the 7th step to determine shows required information, and the three-dimensional geographic pattern that carries out described atural object B shows.
The atural object that the hope of specifying as user shows changes to atural object D, and atural object D comprises atural object A, again in hierarchical clustering tree, searches the new subtree taking described atural object D as tree root; For the node that has created Agent in new subtree in the 5th step and the 6th step, the Agent having created continues to use, and does not need Resurvey and organising data; For the node that does not create Agent in new subtree, create the corresponding Agent of collection or organize Agent, and carrying out corresponding data acquisition and tissue.
Preferably, the method further comprises:
Each gathers the data in the real-time monitor data of Agent pond, and when quantity or the numerical value of the data of finding self required collection change, this collection Agent re-starts data collection task;
Each organizes Agent also to monitor in real time the Agent as its data source, if find have quantity or numerical value change as the Agent in its data source, this tissue Agent re-starts Organization of Data work;
In the time gathering Agent and organize in Agent that the data of any one Agent change, all again according to described in the transformational relation that sets in advance, Agent data after changing are converted to three-dimensional model and show required information, and upgrade the demonstration of corresponding three-dimensional model.
Wherein, preferably, described each node setting identification is proper vector, and the dimension of proper vector starts to increase progressively successively from the tree root of hierarchical clustering tree, and the incremental change of every layer is 1 dimension; For father and son's node, the dimension of supposing child node proper vector is N, the dimension of the proper vector of father node is N-1, and the front N-1 dimensional vector of child node is consistent with the proper vector of its father node, and the N dimensional vector of child node is for distinguishing the each child node under its father node.
Preferably, in described the 5th step, data acquisition is as follows:
First create and gather Agent 1, this collection Agent1 gathers the corresponding data of leaf node according to being identified in data pool, be called leaf node data, using the corresponding mark of first leaf node data gathering as self identification, only gather the data with this mark;
Create again and gather Agent 2, this collection Agent 2 also gathers leaf node data according to being identified in data pool, whether the mark that judges the leaf node data of current collection coincides with the mark of the collection Agent existing, if, gather again leaf node data and judge, otherwise using the mark of the leaf node data of current collection as self identification; Until the collection Agent creating cannot collect the data of new kind, stop creating collection Agent, and the collection Agent without task is cancelled.
Preferably, in described the 6th step, data aggregation process is as follows:
First, create first and organize Agent, be designated as and organize Agent1, this tissue Agent 1 correspondence be the node of row second from the bottom in subtree, organize Agent1 to send inquiry to all collection Agent, obtain the mark of all collection Agent, and be recorded in statistical form; Organize Agent 1 according to mark, find the collection Agent corresponding to all child nodes of self corresponding node, gather Agent and carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of the collection Agent processing is deleted from statistical form;
Then, then create second and organize Agent, be designated as Organization of Data Agent 2, processing procedure is identical with Agent1, until all created organization node for all nodes of row second from the bottom in subtree; Now, the quantity identifying in statistical form is identical with the number of nodes of row second from the bottom;
After this, Agent again founds an organization, be designated as and organize Agent 21, this tissue Agent 21 correspondences be the node of countdown line 3 in subtree, this tissue Agent 21 in statistical form, record institute in a organized way Agent send inquiry, obtain the mark of Agent in a organized way, and be recorded in statistical form; Organize Agent 21 according to mark, find all child nodes of self corresponding node corresponding organize Agent, organize and Agent, carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of organizing Agent of processing is deleted from statistical form; So far the data that completed node layer third from the bottom gather;
Carry out identical establishment for each node layer and organize Agent and carry out the operation that data gather, until handle the root node in subtree.
The present invention also provides a kind of emergent the condition of a disaster situation display system based on multiple agent, and this system comprises cluster cell, database, multiple agent data processing unit, data pool, three-dimensional model render engine and graphical output device; Described multiple agent data processing unit comprises data base administration Agent, interface agent, network data management Agent, data pool, collection Agent processing module, organizes Agent processing module, information transforms Agent;
Described cluster cell, for receiving the remote sensing images in disaster to be shown region, adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, thereby form the hierarchical clustering tree with scale parameter convergence, the each node in hierarchical clustering tree is as a classification; According to outside input, set the represented atural object of each classification and be each node setting identification; This mark unique identification node different classes of on the one hand, but also represent the membership between node;
Interface agent is responsible for carrying out alternately with user, receive user instruction, user instruction comprises the atural object A that hope that user specifies shows, in the hierarchical clustering tree building at cluster cell, search the subtree taking described atural object A as tree root, each node in this subtree is exactly the kind of the information that will extract, and the mark of each node in this subtree is conveyed to respectively to data base administration Agent and network data management Agent; And terrestrial object information to display is sent to three-dimensional model render engine;
Data base administration Agent for according to received mark, extracts the data with receive mark, and keeps in data pool from described database;
In described database, store space environment information and every resource information in disaster to be shown region;
Network data management Agent for according to received mark, extracts the real-time monitored data with receive mark, and keeps in data pool from network;
Data in above-mentioned database and described real-time monitored data are all to have stamped the data of mark;
Gather Agent processing module, for obtaining sub-tree structure from interface agent, obtain the leaf node in described subtree, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified from described data pool;
Organize Agent processing module, for obtaining sub-tree structure from interface agent, set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes, according to mark, finds Agent corresponding to self child node, then gathers the data of all Agent that find, as its data;
Information transforms Agent, is a reaction equation Agent, is converted into the required information of three-dimensional model corresponding to this Agent representative node of demonstration by organizing Agent and gathering the data that in Agent, each Agent obtains;
Three-dimensional model render engine, stores the three-dimensional model corresponding with each node in hierarchical clustering tree, and stores the geographic coordinate of each three-dimensional model; When receive from interface agent idsplay order time, the atural object A that the hope parsing according to interface agent shows, in hierarchical clustering tree, find the corresponding node of this atural object A, utilize information to transform the required information of the each three-dimensional model of demonstration that Agent sends, in conjunction with the geographic coordinate of each three-dimensional model, the three-dimensional geographic pattern that forms described atural object A, sends to graphical output device;
Graphical output device, shows described three-dimensional geographic pattern.
Beneficial effect:
(1) current emergency system framework mostly is the form of " database+data show ", this framework can not be accomplished Real-time Obtaining disaster information, and demonstrations dynamic, many granularities, the variation that particularly shows the landform that caused by geologic hazard, landforms in geologic hazard field can't be carried out real-time renewal and show.For this problem, the present invention adds the intelligent data processing capacity module based on multiple agent between data basis and data demonstration.Therefore, system framework is changed to " database+intelligent data processing+virtual reality shows ".First adopt SSHC algorithm to carry out cluster calculation to remote sensing images, acquisition hierarchical clustering tree, can carry out flexibly, fast data acquisition, tissue and realize and upgrading according to this tree structure, information processing rate is fast like this, thereby can process real time data, and be converted into 3-D view and show, thereby realize dynamic demonstration.
(2) when each Organization of Data, organize out the stalk tree in hierarchical clustering tree, therefore, in the situation that not needing data acquisition again and tissue, the image that can realize many granularities shows.
(3) the present invention has adopted intelligent body to realize intelligent data processing capacity, each Agent has own unique perception, ability and intention, and by certain modality for co-operation common complete a task, design interface of the present invention, collection, tissue and conversion four classes basis Agent, obtain data, to data collections of classify, and the data after collection are set and combined according to level polymerization, its speed is fast, and efficiency is high.
(4) adopt virtual reality technology to show the condition of a disaster, make participant obtain the sense organ the same with real world by Computerized three-dimensional environmental simulation technical construction virtual environment, the formulation of emergent decision-making after calamity is played to booster action.
(5) data acquisition A gent and organize Agent to monitor its Data Source, the real-time the condition of a disaster of obtaining changes related data, can upgrade timely, thereby can realize the demonstration of the condition of a disaster change information if data change.
Demonstration of the present invention is no longer static image or scene, decision-maker is formulated to various emergent decision-makings and play important booster action.Have wide practical use and marketable value in fields such as the simulation of Sudden Geological Hazards the condition of a disaster dangerous situation and emergency preplan simulated maneuvers, have significant contribution effect for effectively protecting people life property safety, reduction economic loss to build emergent support platform to improve Sudden Geological Hazards emergence control level.
Brief description of the drawings
Fig. 1 is the structural representation of hierarchical clustering tree of the present invention.
Fig. 2 is the structural representation of the emergent the condition of a disaster situation system of the present invention.
Fig. 3 is the structural representation of multiple agent data processing unit in the emergent the condition of a disaster situation system of the present invention.
Embodiment
Below in conjunction with accompanying drawing and embodiment, the present invention is described in further detail.
The invention provides a kind of emergent the condition of a disaster situation display packing based on multiple agent, the method comprises the steps:
The 1st step: disaster to be shown region is obtained to remote sensing images, adopt metric space hierarchical cluster (SSHC) algorithm to set up the multiple dimensioned disaggregated model in region to be shown.Wherein, process of establishing is: adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, regulating resolution is scale parameter, to the last converge to a cluster point, thereby form the hierarchical clustering tree with scale parameter convergence, i.e. multiple dimensioned disaggregated model.
In this step, from hierarchical thought, the present invention adopts SSHC algorithm to set up the information classification model changing with Ocular measure.SSHC is a kind of coagulation type hierarchical clustering method, and the method is the laxization process with thermodynamics non-linear dynamic principle simulation human eye vision.Under initial gauges state, in sample space, each sample belongs to a classification, and along with scale parameter changes, the mutual Cluster-Fusion of sample, to the last converges to a cluster point, so just forms the hierarchical clustering tree with scale parameter convergence.
SSHC calculates ratio juris: the kind of all situation informations that system can be shown is information field U, establishes x
ifor a certain class situation information,
suppose x
iafter yardstick γ changes, the equilibrium point of trend is y, x
icontribution margin to y under yardstick γ meets ANALOGY OF BOLTZMANN DISTRIBUTION.
According to thermodynamic principles, (classification results after dimensional variation) entropy maximum in the time that system reaches equilibrium state, and free energy minimization, as shown in formula (1):
Wherein, F is system free energy, and e (x) is energy function.Formula (1) is derived, has:
Formula (2) illustrates that, in the situation that yardstick γ is certain, x can converge to a fixed value y by the iteration of certain number of times.Y is the new cluster centre of x value under yardstick γ, i.e. x, and y has causality and y is made up of some x.
In SSHC model, what time following all element α that can show in system, meet:
1, under initial gauges,
2, in the time that yardstick changes,
3, in the time that yardstick is maximum,
wherein Y is final convergence result.
Therefore, α, x, y can adopt the set membership in tree construction to represent, when completing after cluster at different scale, just can obtain hierarchical clustering tree, and the bottom node of this hierarchical clustering tree is α, and intermediate node is y
i, root node is Y, the corresponding yardstick of each level.Identity element α has had multiple dimensioned classification results like this, can carry out varigrained displaying to element α according to yardstick γ.
While adopting SSHC algorithm for remote sensing images so, adopt the yardstick γ of image resolution ratio as SSHC algorithm, the corresponding sighting distance of each yardstick.Adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, this best result distinguishes to be that lowest scale is artificial appointment, this and the most fine-grained atural object relevant (atural object refers to ground visible oBject, for example street, crossroad etc.) of wishing to obtain, along with scale parameter changes, the mutual Cluster-Fusion of sample, to the last converges to a cluster point, and this cluster point is the highest yardstick, it is the atural object of granularity maximum in image, for example whole mountain region; Through the hierarchical clustering tree that repeatedly thereby polymerization formation restrains with scale parameter, i.e. multiple dimensioned disaggregated model.
In hierarchical clustering tree, the highest yardstick and lowest scale are root node and the leaf nodes of hierarchical clustering tree, the corresponding yardstick of every one deck in hierarchical clustering tree, and the node in every layer represents the cluster centre that under this layer of yardstick, cluster forms.The scale span of cluster process can be by artificially determining, that divides is thinner, and the level that can show when demonstration is just more.
The 2nd step: using the each node in hierarchical clustering tree as a classification, set the represented atural object of each classification, and be that each node is set proper vector, this proper vector is used for the membership between identification nodes, thereby can know which kind of node belongs in whole hierarchical clustering tree.
Aforementioned the 1st step is only to carry out cluster for remote sensing images, obtains hierarchical clustering tree, but the each cluster centre in every one deck does not still have concrete implication.Need below manually to give a concrete characters of ground object to each cluster centre.
For example, carry out cluster for a remote sensing map that is seated the cities and towns in mountain region, obtain hierarchical clustering tree as shown in Figure 1, this hierarchical clustering tree only shows part branch, in some, the child node of node layer does not draw, the number of plies of descendants's node of in fact all middle node layers is identical, because cluster is from bottom to top.So in this step, need to be using the each node in this clustering tree as a classification, although there is membership between the node of levels, but due to the difference of yardstick, therefore they are regarded as to different classifications, set the represented atural object of each classification, in the time setting, notice that the atural object of father and son's node is also set membership.For example, the child node of x2 comprises x21, x22, x23, and x2 is set as to residential block, and x21, x22, x23 are set as respectively to residential quarters, business block and factory district.
For the ease of follow-up Data classification and tissue, in this step, also need for each node setting identification this mark unique identification node different classes of on the one hand, but also can represent the membership between node, thereby can know the position of node in whole hierarchical clustering tree.
In practice, vector is the one mark of commonly using, and its design comparison is flexible, and is convenient to computing machine identification, and occupies little space.In the embodiment shown in fig. 1, adopt vector as described mark, be called proper vector.Proper vector is multidimensional, and its dimension has represented node place level, and the dimension of proper vector starts to increase progressively successively from tree root, and incremental change is 1 dimension, and preferably tree root is since 1 dimension; For father and son's node, the dimension of supposing child node proper vector is N, the dimension of father node proper vector is N-1 so, and the front N-1 dimensional vector of child node is consistent with the proper vector of its father node, and the N dimensional vector of child node is for distinguishing the each child node under this father node.As shown in Figure 1, the proper vector of x2 is (0,0,1), and the proper vector of its child node x21, x22, x23 is respectively (0,0,1,0), (0,0,1,1), (0,0,1,2).
Visible, the setting of this proper vector, can identify the membership between node, thereby can know the position of node in whole yardstick disaggregated model.
The 3rd step: for the each node in hierarchical clustering tree, set up the three-dimensional model of the represented atural object of the classification of this node, and according to the geographic coordinate of the each three-dimensional model of atural object set positions in remote sensing images; This geographic coordinate for showing three-dimensional geographic pattern in the 8th step in image in conjunction with three-dimensional model.
Still, taking Fig. 1 as example, set up the three-dimensional model of residential block for node x2, set up respectively the three-dimensional model of residential quarters, business block, factory district for node x21, x22, x23.In this three-dimensional model, defined the information that shows that this three-dimensional model is required, these information are follow-up by gathering Agent and organizing Agent to gather and tissue, then obtain through transforming.
Three-dimensional modeling need to be used landform source data, and landform source data is digital elevation data, and its acquisition methods has following several: 1) adopt geodesic method directly to measure elevation from landform; 2) utilize photogrammetric measurement photo, adopt digital elevation to judge that instrument reads elevation from two corresponding photos; 3) utilize satellite photogrammetry photo to read altitude figures (remote sensing); 4) read altitude figures from the common contour map of small scale; 5) extract the landform altitude data of desired zone from existing map data base.MultiGen Creator software can directly extract interested landform altitude data and comprise the dem data of USGS (USGS) or the DTED data of image map office of the U.S. (NIMA), and converts the special DED data layout of Creator to and carry out dimensional topography modeling.
The 4th step: when actual the condition of a disaster situation shows, receives user's, user instruction comprises the atural object A that hope that user specifies shows, searches the atural object A that shows taking the hope subtree as tree root in hierarchical clustering tree.
For example, user wishes to show residential block x2, in hierarchical clustering tree, searches the subtree taking x2 as tree root, and descendants's node of x2 comprises x21 and descendants's node, x22 and descendants's node thereof, x23 and descendants's node thereof.
Described descendants's node refers to father node have all child nodes of membership, child node of child node etc. herein, and child node just refers to the child node that has direct set membership with father node, does not comprise interlayer child node.
The 5th step: the data acquisition based on Agent group:
Obtain the node of the bottom in the subtree that the 4th step finds, i.e. leaf node.Set up one for each leaf node and gather Agent, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified; The data source that gathers Agent image data comprise be temporary in data pool from the data in database, and from outside real-time monitored data; Data in described database and described real-time monitored data are all to have stamped the data of mark.
Wherein, Agent is the English of intelligent body, and Agent has independence, communication, reactivity and cooperative functional module, and the subtask that multi-agent system (MAS) is carried out based on several Agent cooperatively interacts, and completes its predetermined general assignment.The present invention adopts the acquisition module of Agent as this step, can improve data acquisition efficiency, and each module completes the data acquisition of self type.
Data source in the present invention comprises database, real-time monitored data.Database is responsible for record space environmental information and every resource information etc., and these are all that three-dimensional model shows required information, and the content in database can be upgraded according to actual conditions.Real-time monitored data refer to the image that the various information obtaining in network environment comprises that data, satellite remote sensing images, the unmanned plane near-earth of various kinds of sensors are taken and all kinds of real-time information that processing draws through image etc., and this category information is also that three-dimensional model shows required information.This two category information has all carried out adding the processing of mark in advance, and collection Agent only gathers those the data of mark.
In data acquisition:
First, create first and gather Agent---gather Agent1, this collection Agent 1 gathers the corresponding data of leaf node according to being identified in data pool, be called leaf node data, using the corresponding mark of first leaf node data gathering as self identification, only gather the data with this mark;
Then, create two and gather Agent---gather Agent 2, this collection Agent 2 also gathers leaf node data according to being identified in data pool, whether the mark that judges the leaf node data of current collection coincides with the mark of the collection Agent existing, if, gather again leaf node data and judge, otherwise using the mark of the leaf node data of current collection as self identification;
Constantly create new collection Agent, until the collection Agent creating cannot collect the data of new kind, stop creating collection Agent, and the collection Agent without task is cancelled.Like this, by the data category in data pool separately, belong to respectively different collection Agent and be responsible for.
The 6th step: the Organization of Data based on Agent group:
Set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes is according to mark, find self correspondence all child nodes Agent(for node layer second from the bottom corresponding organize Agent, the Agent of corresponding child node is for gathering Agent, for layer third from the bottom and with upper layer node corresponding organize Agent, the Agent of corresponding child node is for organizing Agent), then gather the data of the Agent finding, as its data.Organizing the data of Agent to gather is from bottom to top, is first gathered by the Agent that organizes of lower floor, then gathered by the Agent that organizes on upper strata.
When described while being designated aforesaid proper vector, suppose that organizing the proper vector of Agent is N dimension, to search proper vector be N+1 dimension to this tissue Agent, and front N dimensional feature vector is with the vectorial identical collection Agent of unique characteristics or organize Agent, then gather the data of the Agent finding, as its data.
Still taking Fig. 1 as example, the data of the collection Agent that what x23 was corresponding organize Agent gathers x231 and x232 is corresponding, what x2 was corresponding organizes Agent to gather x21, x22 and the data of organizing Agent corresponding to x23.
In Organization of Data process:
First, create first and organize Agent---organize Agent 1, this tissue Agent 1 correspondence be the node of row second from the bottom in subtree, organize Agent 1 to send inquiry to all collection Agent, obtain the mark of all collection Agent, and be recorded in statistical form.Organize Agent 1 according to mark, find the collection Agent corresponding to all child nodes of self corresponding node, gather Agent and carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of the collection Agent processing is deleted from statistical form.If be designated proper vector, find proper vector than unique characteristics vector length 1, and the front N-1 dimensional feature vector proper vector identical with unique characteristics vector, and find corresponding collection Agent, gather Agent and carry out Data Collection from these, and gather.
Then, then create second and organize Agent---Organization of Data Agent 2, processing procedure is identical with Agent 1, until all created organization node for all nodes of row second from the bottom in subtree; Now, the quantity identifying in statistical form is identical with the number of nodes of row second from the bottom;
After this, Agent again founds an organization, be designated as and organize Agent 21, this tissue Agent 21 correspondences be the node of countdown line 3 in subtree, this tissue Agent 21 in statistical form, record institute in a organized way Agent send inquiry, obtain the mark of Agent in a organized way, and be recorded in statistical form.Organize Agent 21 according to mark, find all child nodes of self corresponding node corresponding organize Agent, organize and Agent, carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of organizing Agent of processing is deleted from statistical form; So far the data that completed node layer third from the bottom gather;
Carry out identical establishment for each node layer and organize Agent and carry out the operation that data gather, until handle the root node in subtree.
The 7th step: according to the transformational relation setting in advance, the data of organizing each Agent acquisition in Agent and collection Agent are converted into and show that the three-dimensional model corresponding to node of this Agent representative shows required information.
The 8th step: the atural object A that the hope of specifying according to the 4th step user shows, in hierarchical clustering tree, find the corresponding node of this atural object A, the each three-dimensional model that utilizes the 7th step to determine shows required information, the three-dimensional geographic pattern that carries out described atural object A shows.
The 9th step: the atural object that the hope of specifying as user shows changes to the atural object B that in described subtree, a certain node is corresponding, without again carrying out data acquisition and tissue, the each three-dimensional model that directly utilizes the 7th step to determine shows required information, and the three-dimensional geographic pattern that carries out described atural object B shows.
Visible, know clearly after data acquisition and tissue when completing for a subtree taking atural object A as root node, atural object A and more fine-grained atural object thereof be can show, and data acquisition and tissue do not needed to re-start.Thereby data processing and demonstration are fast realized.
When needs show atural object C, and atural object C do not comprise atural object A, redefines new subtree, starts to re-execute the operation of step 4 ~ 8 from step 4.
In the time that needs show the atural object D of coarsegrain more, and atural object D comprises atural object A, can redefine equally new subtree, starts to re-execute the operation of step 4 ~ 8 from step 4.But in order to reduce the processing time, preferably, again in hierarchical clustering tree, search the new subtree taking described atural object D as tree root, for the node that has created Agent in new subtree in the 5th step and the 6th step, the Agent creating can continue to use, and does not need Resurvey and organising data, for the part that does not create Agent in new subtree, create Agent, and carry out corresponding data acquisition and tissue.The process of data acquisition and tissue is identical with the mode described in the 5th step and the 6th step.
Each gathers also real-time data in monitor data pond of Agent, in the time finding the data variation of self required collection, and for example number change, numerical value change, this collection Agent re-starts data collection task; In like manner, each organizes Agent also to monitor in real time the Agent as its data source, if find have quantity or numerical value change as the Agent in its data source, this tissue Agent re-starts Organization of Data work; In the time gathering Agent and organize in Agent that the data of any one Agent change, all, again according to the transformational relation setting in advance, be converted to three-dimensional model and show required information, and upgrade the demonstration of corresponding three-dimensional model.
The present invention also provides a kind of display system that can realize the above-mentioned emergent the condition of a disaster situation display packing based on multiple agent.As shown in Figure 2, this system comprises cluster cell, database, multiple agent data processing unit, three-dimensional model render engine and graphical output device.
As shown in Figure 3, this multiple agent data processing unit comprises data base administration Agent, interface agent, network data management Agent, data pool, collection Agent processing module, organizes Agent processing module and information to transform Agent.
Below the function of each module is described in detail.
Cluster cell, for receiving the remote sensing images in disaster to be shown region, adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, thereby form the hierarchical clustering tree with scale parameter convergence, the each node in hierarchical clustering tree is as a classification; According to outside input, set the represented atural object of each classification and be each node setting identification; This mark unique identification node different classes of on the one hand, but also represent the membership between node.This mark can adopt aforesaid proper vector.
Interface agent is responsible for carrying out alternately with user, receive user instruction, user instruction comprises the atural object A that hope that user specifies shows, in the hierarchical clustering tree building at cluster cell, search the subtree taking described atural object A as tree root, each node in this subtree is exactly the kind of the information that will extract, and the mark of each node in this subtree is conveyed to respectively to data base administration Agent and network data management Agent; And terrestrial object information to display is sent to three-dimensional model render engine.
Data base administration Agent for according to received mark, extracts the data with receive mark, and keeps in data pool from described database.
Network data management Agent for according to received mark, extracts the real-time monitored data with receive mark, and keeps in data pool from network.
In described database, store space environment information and every resource information in disaster to be shown region.
Data in above-mentioned database and described real-time monitored data are all to have stamped the data of mark.
Gather Agent processing module, for obtaining sub-tree structure from interface agent, obtain the leaf node in described subtree, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified from described data pool.
In data acquisition, first create and gather Agent 1, this Agent 1 carries out data acquisition according to proper vector, is as the criterion with first data class that it was gathered, and only gathers the data of this kind; Now, then create Agent 2, carry out data acquisition, and Agent 1 is inquired, both gather same class data its, are to change class data, no, continue to gather this category information; Until the Agent creating cannot collect the data of new kind, stop creating Agent, and the Agent without task is cancelled.Like this, by the data category in data pool separately, belong to respectively different collection Agent and be responsible for.
Organize Agent processing module, for obtaining sub-tree structure from interface agent, set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes, according to mark, finds Agent corresponding to self child node, then gathers the data of all Agent that find, as its data.
In Organization of Data process, first organize Agent1 by establishment equally, it is to all collection Agent and organize Agent to send inquiry, inquires its data class, in fact be exactly to inquire its proper vector, and the corresponding relation of each Agent and proper vector is recorded in statistical form.According to the proper vector of recording in this statistical form, find proper vector than unique characteristics vector length 1, and the front N-1 dimensional feature vector proper vector identical with unique characteristics vector, and find corresponding Agent, from these Agent, carry out Data Collection, and gather.Then its collected data class characteristic of correspondence vector is deleted from statistical form.System creates Organization of Data Agent 2 more afterwards, and processing procedure is identical with Agent 1.Until in statistical form without proper vector.
Information transforms Agent, is a reaction equation Agent, is converted into the required information of three-dimensional model corresponding to this Agent representative node of demonstration by organizing Agent and gathering the data that in Agent, each Agent obtains.
Three-dimensional model render engine, stores the three-dimensional model corresponding with each node in hierarchical clustering tree, and stores the geographic coordinate of each three-dimensional model; When receive from interface agent idsplay order time, the atural object A that the hope parsing according to interface agent shows, in hierarchical clustering tree, find the corresponding node of this atural object A, utilize information to transform the required information of the each three-dimensional model of demonstration that Agent sends, in conjunction with the geographic coordinate of each three-dimensional model, the three-dimensional geographic pattern that forms described atural object A, sends to graphical output device.This three-dimensional model render engine can adopt the Terrain tool box that Creator modeling software provides to make ground model, plays up the bag MultiGen Vega 3.7.1 that develops software and realize the virtual reality Presentation Function of system by calling three-dimensional picture based on OpenGL.
Graphical output device, shows described three-dimensional geographic pattern.
Interface agent receives after user instruction again, the atural object that the hope of specifying when user instruction shows changes to the atural object B that in described subtree, a certain node is corresponding, interface agent is to passing on network data management Agent and data base administration Agent to pass on fresh information, directly send instruction to three-dimensional model render engine, notice three-dimensional model render engine forms the three-dimensional geographic pattern of atural object B, sends to graphical output device.
Interface agent receives after user instruction again, and the atural object that the hope of specifying as user shows changes to atural object D, and atural object D comprises atural object A, again in hierarchical clustering tree, searches the new subtree taking described atural object D as tree root; More described subtree and described new subtree, for the new node increasing in new subtree, convey to respectively data base administration Agent and network data management Agent by the mark of new node, is that new node is collected data by these two Agent, is put in data pool; And send instruction to three-dimensional model render engine, notice three-dimensional model render engine forms the three-dimensional geographic pattern of atural object D, sends to graphical output device.In addition, gather Agent processing module and organize Agent processing module according to new subtree, for the node that has created Agent in new subtree, the Agent having created continues to use, and does not need Resurvey and organising data; For the node that does not create Agent in new subtree, create the corresponding Agent of collection or organize Agent, and carrying out corresponding data acquisition and tissue.
Preferably, each gathers the data in the real-time monitor data of Agent pond, and when quantity or the numerical value of the data of finding self required collection change, this collection Agent re-starts data collection task;
Meanwhile, each organizes Agent also to monitor in real time the Agent as its data source, if find have quantity or numerical value change as the Agent in its data source, this tissue Agent re-starts Organization of Data work;
So, in the time gathering Agent and organize in Agent that the data of any one Agent change, all notify three-dimensional model render engine again the Agent data after changing to be converted to three-dimensional model and show required information, and upgrade three-dimensional geographic pattern, send to graphical output device.
From the above, the present invention is based on the emergent the condition of a disaster situation display system of multiple agent, the function of this system can be summarized as the real-time information of obtaining the condition of a disaster, utilize the Agent that each function is different to carry out a series of information processing, and finally adopt virtual reality technology to carry out dynamically, overall situation shows fast.Multi-agent Technology is combined with virtual reality technology and realize intelligent data processing and quick Presentation Function.Each Agent has own unique perception, ability and intention, and by certain modality for co-operation common complete a task, and virtual reality technology refers to by Computerized three-dimensional environmental simulation technical construction virtual environment and makes participant obtain the sense organ the same with real world.The present invention relates to interface, collection, tissue and conversion four class basis Agent, realized from data to the process that shows information by the cooperation between them.
As can be seen here, the present invention is directed to the problem of prior art, between data basis and data demonstration, add the intelligent data processing capacity module based on multiple agent.Therefore, system framework is changed to " database+intelligent data processing+virtual reality shows ".The function of intelligent data processing is to realize from mass data information intelligence, extract related data fast, and transforms into the information that directly can be shown by VR-Platform.
In sum, these are only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (10)
1. the emergent the condition of a disaster situation display packing based on multiple agent Agent, is characterized in that, comprising:
The 1st step: disaster to be shown region is obtained to remote sensing images, adopt metric space hierarchical cluster SSHC algorithm to set up multiple dimensioned disaggregated model;
Described process of establishing is: adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, regulating resolution is scale parameter, to the last converge to a cluster point, thereby form the hierarchical clustering tree with scale parameter convergence, i.e. multiple dimensioned disaggregated model;
The 2nd step: using the each node in hierarchical clustering tree as a classification, set the represented atural object of each classification; For each node setting identification, this mark unique identification node different classes of on the one hand, but also represent the membership between node;
The 3rd step: according to hierarchical clustering tree, set up three-dimensional model corresponding to each classification in each layer, and according to the geographic coordinate of the each three-dimensional model of atural object set positions in remote sensing images; This geographic coordinate for showing three-dimensional geographic pattern in the 8th step in image in conjunction with three-dimensional model;
The 4th step: when actual the condition of a disaster situation shows, receive user instruction, user instruction comprises the atural object A that hope that user specifies shows is searched the atural object A that shows taking the described hope subtree as tree root in hierarchical clustering tree;
The 5th step: the data acquisition based on Agent group:
Obtain the leaf node in described subtree; Set up one for each leaf node and gather Agent, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified; The data source that gathers Agent image data is the two class data that are temporary in data pool, and a class is from database, and another kind of is from outside real-time monitored data; Data in described database and described real-time monitored data are all to have stamped the data of mark;
The 6th step: the Organization of Data based on Agent group:
Set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes, according to mark, finds Agent corresponding to self child node, then gathers the data of all Agent that find, as its data;
The 7th step: according to the transformational relation setting in advance, be converted into by organizing Agent and gathering the data that in Agent, each Agent obtains the required information of three-dimensional model corresponding to node that shows this Agent representative;
The 8th step: the atural object A that the hope of specifying according to the 4th step user shows, in hierarchical clustering tree, find the corresponding node of this atural object A, the each three-dimensional model that utilizes the 7th step to determine shows required information, forms the three-dimensional geographic pattern of described atural object A and shows;
The 9th step: the atural object that the hope of specifying as user shows changes to the atural object B that in described subtree, a certain node is corresponding, without again carrying out data acquisition and tissue, the each three-dimensional model that directly utilizes the 7th step to determine shows required information, and the three-dimensional geographic pattern that carries out described atural object B shows.
2. the method for claim 1, is characterized in that, the method further comprises:
The atural object that the hope of specifying as user shows changes to atural object D, and atural object D comprises atural object A, again in hierarchical clustering tree, searches the new subtree taking described atural object D as tree root; For the node that has created Agent in new subtree in the 5th step and the 6th step, the Agent having created continues to use, and does not need Resurvey and organising data; For the node that does not create Agent in new subtree, create the corresponding Agent of collection or organize Agent, and carrying out corresponding data acquisition and tissue.
3. method as claimed in claim 1 or 2, is characterized in that, the method further comprises:
Each gathers the data in the real-time monitor data of Agent pond, and when quantity or the numerical value of the data of finding self required collection change, this collection Agent re-starts data collection task;
Each organizes Agent also to monitor in real time the Agent as its data source, if find have quantity or numerical value change as the Agent in its data source, this tissue Agent re-starts Organization of Data work;
In the time gathering Agent and organize in Agent that the data of any one Agent change, all again according to described in the transformational relation that sets in advance, Agent data after changing are converted to three-dimensional model and show required information, and upgrade the demonstration of corresponding three-dimensional model.
4. the method for claim 1, is characterized in that, described each node setting identification is proper vector, and the dimension of proper vector starts to increase progressively successively from the tree root of hierarchical clustering tree, and the incremental change of every layer is 1 dimension; For father and son's node, the dimension of supposing child node proper vector is N, the dimension of the proper vector of father node is N-1, and the front N-1 dimensional vector of child node is consistent with the proper vector of its father node, and the N dimensional vector of child node is for distinguishing the each child node under its father node.
5. the method for claim 1, it is characterized in that, in described the 5th step, first create and gather Agent1, this collection Agent1 gathers the corresponding data of leaf node according to being identified in data pool, be called leaf node data, using the corresponding mark of first leaf node data gathering as self identification, only gather the data with this mark;
Create again and gather Agent2, this collection Agent2 also gathers leaf node data according to being identified in data pool, whether the mark that judges the leaf node data of current collection coincides with the mark of the collection Agent existing, if, gather again leaf node data and judge, otherwise using the mark of the leaf node data of current collection as self identification; Until the collection Agent creating cannot collect the data of new kind, stop creating collection Agent, and the collection Agent without task is cancelled.
6. the method for claim 1, it is characterized in that, in described the 6th step, first, create first and organize Agent, be designated as and organize Agent1, what this tissue Agent1 was corresponding is the node of row second from the bottom in subtree, organize Agent1 to send inquiry to all collection Agent, obtain the mark of all collection Agent, and be recorded in statistical form; Organize Agent1 according to mark, find the collection Agent corresponding to all child nodes of self corresponding node, gather Agent and carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of the collection Agent processing is deleted from statistical form;
Then, then create second and organize Agent, be designated as and organize Agent2, processing procedure with organize Agent1 identical, until all created organization node for all nodes of row second from the bottom in subtree; Now, the quantity identifying in statistical form is identical with the number of nodes of row second from the bottom;
After this, then the Agent that founds an organization, be designated as and organize Agent21, what this tissue Agent21 was corresponding is the node of countdown line 3 in subtree, this tissue Agent21 to the institute recording in statistical form in a organized way Agent send inquiry, obtain the mark of Agent in a organized way, and be recorded in statistical form; Organize Agent21 according to mark, find all child nodes of self corresponding node corresponding organize Agent, organize and Agent, carry out Data Collection and gather from these, and the mark of self is added in statistical form, the mark of organizing Agent of processing is deleted from statistical form; So far the data that completed node layer third from the bottom gather;
Carry out identical establishment for each node layer and organize Agent and carry out the operation that data gather, until handle the root node in subtree.
7. the emergent the condition of a disaster situation display system based on multiple agent, is characterized in that, this system comprises cluster cell, database, multiple agent data processing unit, three-dimensional model render engine and graphical output device; Described multiple agent data processing unit comprises data base administration Agent, interface agent, network data management Agent, data pool, collection Agent processing module, organizes Agent processing module, information transforms Agent;
Described cluster cell, for receiving the remote sensing images in disaster to be shown region, adopt the yardstick γ of image resolution ratio as SSHC algorithm, adopt SSHC algorithm to start cluster calculation to remote sensing images from the highest resolution of specifying, thereby form the hierarchical clustering tree with scale parameter convergence, the each node in hierarchical clustering tree is as a classification; According to outside input, set the represented atural object of each classification and be each node setting identification; This mark unique identification node different classes of on the one hand, but also represent the membership between node;
Interface agent is responsible for carrying out alternately with user, receive user instruction, user instruction comprises the atural object A that hope that user specifies shows, in the hierarchical clustering tree building at cluster cell, search the subtree taking described atural object A as tree root, each node in this subtree is exactly the kind of the information that will extract, and the mark of each node in this subtree is conveyed to respectively to data base administration Agent and network data management Agent; And terrestrial object information to display is sent to three-dimensional model render engine;
Data base administration Agent for according to received mark, extracts the data with receive mark, and keeps in data pool from described database;
In described database, store space environment information and every resource information in disaster to be shown region;
Network data management Agent for according to received mark, extracts the real-time monitored data with receive mark, and keeps in data pool from network;
Data in above-mentioned database and described real-time monitored data are all to have stamped the data of mark;
Gather Agent processing module, for obtaining sub-tree structure from interface agent, obtain the leaf node in described subtree, corresponding leaf node and collection Agent share like-identified; Each collection Agent is responsible for gathering and the data self with like-identified from described data pool;
Organize Agent processing module, for obtaining sub-tree structure from interface agent, set up one for the each node of other except leaf node in described subtree and organize Agent, corresponding node and organize Agent to share like-identified; Each Agent that organizes, according to mark, finds Agent corresponding to self child node, then gathers the data of all Agent that find, as its data;
Information transforms Agent, is a reaction equation Agent, is converted into the required information of three-dimensional model corresponding to this Agent representative node of demonstration by organizing Agent and gathering the data that in Agent, each Agent obtains;
Three-dimensional model render engine, stores the three-dimensional model corresponding with each node in hierarchical clustering tree, and stores the geographic coordinate of each three-dimensional model; When receive from interface agent idsplay order time, the atural object A that the hope parsing according to interface agent shows, in hierarchical clustering tree, find the corresponding node of this atural object A, utilize information to transform the required information of the each three-dimensional model of demonstration that Agent sends, in conjunction with the geographic coordinate of each three-dimensional model, the three-dimensional geographic pattern that forms described atural object A, sends to graphical output device;
Graphical output device, shows described three-dimensional geographic pattern.
8. system as claimed in claim 7, it is characterized in that, interface agent receives user instruction again, the atural object that the hope of specifying when user instruction shows changes to the atural object B that in described subtree, a certain node is corresponding, interface agent is to passing on network data management Agent and data base administration Agent to pass on fresh information, directly send instruction to three-dimensional model render engine, notice three-dimensional model render engine forms the three-dimensional geographic pattern of atural object B, sends to graphical output device.
9. system as claimed in claim 7 or 8, it is characterized in that, interface agent receives user instruction again, and the atural object that the hope of specifying as user shows changes to atural object D, and atural object D comprises atural object A, again in hierarchical clustering tree, search the new subtree taking described atural object D as tree root; More described subtree and described new subtree, for the new node increasing in new subtree, convey to respectively data base administration Agent and network data management Agent by the mark of new node; And send instruction to three-dimensional model render engine, notice three-dimensional model render engine forms the three-dimensional geographic pattern of atural object D, sends to graphical output device;
Gather Agent processing module and organize Agent processing module according to new subtree, for the node that has created Agent in new subtree, the Agent having created continues to use, and does not need Resurvey and organising data; For the node that does not create Agent in new subtree, create the corresponding Agent of collection or organize Agent, and carrying out corresponding data acquisition and tissue.
10. system as claimed in claim 7 or 8, is characterized in that, each gathers the data in the real-time monitor data of Agent pond, and when quantity or the numerical value of the data of finding self required collection change, this collection Agent re-starts data collection task;
Each organizes Agent also to monitor in real time the Agent as its data source, if find have quantity or numerical value change as the Agent in its data source, this tissue Agent re-starts Organization of Data work;
In the time gathering Agent and organize in Agent that the data of any one Agent change, all notify three-dimensional model render engine again the Agent data after changing to be converted to three-dimensional model and show required information, and upgrade three-dimensional geographic pattern, send to graphical output device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210202747.6A CN102800120B (en) | 2012-06-15 | 2012-06-15 | Emergency disaster situation display system and method based on multiple intelligent bodies |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210202747.6A CN102800120B (en) | 2012-06-15 | 2012-06-15 | Emergency disaster situation display system and method based on multiple intelligent bodies |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102800120A CN102800120A (en) | 2012-11-28 |
| CN102800120B true CN102800120B (en) | 2014-07-16 |
Family
ID=47199217
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210202747.6A Active CN102800120B (en) | 2012-06-15 | 2012-06-15 | Emergency disaster situation display system and method based on multiple intelligent bodies |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102800120B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049514B (en) * | 2012-12-14 | 2016-08-10 | 杭州淘淘搜科技有限公司 | A kind of equilibrium image clustering method based on hierarchical cluster |
| CN105654535B (en) * | 2014-11-14 | 2018-08-31 | 中国科学院沈阳计算技术研究所有限公司 | A kind of model manager system for three-dimensional simulation system |
| CN108399104B (en) * | 2018-01-30 | 2021-09-28 | 西安电子科技大学 | Multi-Agent-based elastic and telescopic task planning system and method |
| CN110910511B (en) * | 2019-11-28 | 2021-09-17 | 北京航空航天大学 | Search and rescue flow simulation and interaction system and method based on mixed reality |
| CN113255920B (en) * | 2021-06-29 | 2021-09-28 | 中国科学院自动化研究所 | Big data based dynamic system disaster cause and effect inference method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5193185A (en) * | 1989-05-15 | 1993-03-09 | David Lanter | Method and means for lineage tracing of a spatial information processing and database system |
| CN101515309A (en) * | 2009-04-07 | 2009-08-26 | 华中科技大学 | City emergency evacuation simulation system based on multi intelligent agent |
| CN101930652A (en) * | 2010-08-17 | 2010-12-29 | 丁增辉 | Agent technology-based fire alarm system and method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8884964B2 (en) * | 2008-04-22 | 2014-11-11 | Exxonmobil Upstream Research Company | Functional-based knowledge analysis in a 2D and 3D visual environment |
-
2012
- 2012-06-15 CN CN201210202747.6A patent/CN102800120B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5193185A (en) * | 1989-05-15 | 1993-03-09 | David Lanter | Method and means for lineage tracing of a spatial information processing and database system |
| CN101515309A (en) * | 2009-04-07 | 2009-08-26 | 华中科技大学 | City emergency evacuation simulation system based on multi intelligent agent |
| CN101930652A (en) * | 2010-08-17 | 2010-12-29 | 丁增辉 | Agent technology-based fire alarm system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102800120A (en) | 2012-11-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN100533486C (en) | Digital city full-automatic generating method | |
| CN101149843B (en) | Succession type automatic generation and real time updating method for digital city | |
| CN110222137B (en) | Intelligent campus system based on oblique photography and augmented reality technology | |
| CN102800120B (en) | Emergency disaster situation display system and method based on multiple intelligent bodies | |
| CN107679229A (en) | The synthetical collection and analysis method of city three-dimensional building high-precision spatial big data | |
| CN108182724B (en) | High-precision urban heat island detection method and device and storage device | |
| CN113066183A (en) | Virtual scene generation method and device, computer equipment and storage medium | |
| Saeidi et al. | Assessing the visual impacts of new urban features: Coupling visibility analysis with 3D city modelling | |
| Sanson et al. | Geographic information systems: their application in animal disease control | |
| Khayyal et al. | Creation and spatial analysis of 3D city modeling based on GIS data | |
| Kostrikov et al. | Human geography with geographical information systems | |
| Shirowzhan et al. | Developing metrics for quantifying buildings’ 3D compactness and visualizing point cloud data on a web-based app and dashboard | |
| KR20210054408A (en) | Apparatus and method for modeling using gis | |
| CN114676299A (en) | 3D visualization display method and system for classical garden knowledge graph | |
| Ying et al. | Web visualization of geo-spatial data using SVG and VRML/X3D | |
| Zhu et al. | Unified Representation of three dimensional city models | |
| Zhan et al. | Research and practice on disaster prevention planning in villages based on planning support system overview: Potential public policies on spatial planning for sustainable urban forms a Case Study | |
| CN116108124B (en) | Land type similarity determination method, system, equipment and medium based on GIS | |
| CN114818310B (en) | Forest landscape simulation method and device, electronic equipment and storage medium | |
| Fotheringham et al. | Geographic information science: an introduction | |
| Mihai et al. | UAV TECHNOLOGY USED IN FACILITY MANAGEMENT IN THE CAMPUS OF THE BUCHAREST UNIVERSITY OF AGRICULTURAL SCIENCES AND VETERINARY MEDICINE | |
| Shao | Baselining UBC Vancouver Campus Urban Forest and Land Use: Developing and Validating Up-to-date Tree Inventory and Land Classification Map of the UBC Vancouver Campus | |
| Garg | Understanding Geospatial Data | |
| Zhang et al. | Research on land use/cover classification based on RS and GIS | |
| Cheng | Structure of Digital Landscape Architecture |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |