CN102800120A - 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 PDF

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CN102800120A
CN102800120A CN2012102027476A CN201210202747A CN102800120A CN 102800120 A CN102800120 A CN 102800120A CN 2012102027476 A CN2012102027476 A CN 2012102027476A CN 201210202747 A CN201210202747 A CN 201210202747A CN 102800120 A CN102800120 A CN 102800120A
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CN102800120B (en
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陈杰
于海心
张娟
陈晨
竺文彬
连晓岩
陈是君
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Beijing Institute of Technology BIT
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Abstract

本发明公开了一种基于多智能体的应急灾情态势显示系统和方法,能够实时获取灾害信息,并动态、多粒度的三维显示。该方法包括:采用SSHC算法处理遥感图像建立层次聚类树;层次聚类树中的每个节点为一个类别,设定各类别对应的地物,并建立每个类别的三维模型;灾情态势显示时,接收用户指令,用户指令包括用户指定的希望显示的地物A,在层次聚类树中查找以所述希望显示的地物A为树根的子树;创建采集智能体收集子树中底层节点的数据,创建组织智能体从采集智能体或其他组织智能体中汇总除底层节点之外的其他各级节点的数据。根据每个节点的数据渲染各类三维模型,形成地物A的三维地理图像并显示,并且可以显示地物A内部更细粒度的三维地理图像。

The invention discloses a multi-agent based emergency disaster situation display system and method, capable of real-time acquisition of disaster information and dynamic, multi-granularity three-dimensional display. The method includes: using the SSHC algorithm to process remote sensing images to establish a hierarchical clustering tree; each node in the hierarchical clustering tree is a category, setting the corresponding ground objects of each category, and establishing a three-dimensional model of each category; displaying the disaster situation When receiving the user instruction, the user instruction includes the feature A that the user specifies and wants to display, and searches for the subtree rooted at the feature A that is desired to be displayed in the hierarchical clustering tree; creates the collection agent to collect the subtree For the data of the underlying nodes, the organization agent is created to summarize the data of nodes at other levels except the underlying nodes from the collection agent or other organizational agents. Render various 3D models according to the data of each node, form and display the 3D geographic image of object A, and display the finer-grained 3D geographic image inside object A.

Description

A kind of emergent the condition of a disaster situation display system and method based on multiple agent
Technical field
The invention belongs to three-dimensional situation and show the 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 is meant on the basis of disaster knowledge, utilizes database technology, geographic information system technology, based on causality analysis and decision-making corresponding relation, sets up the process of estimating final formulation emergency preplan from dynamic demonstration, the disaster of disaster.For effectively protecting the people life property safety, reducing economic loss, China begins progressively to carry out the emergency system research towards disaster as far back as early 1990s.Along with the calamity emergency system that constantly develops into of space technology, infotech, virtual reality technology has 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 information of the condition of a disaster; Thereby increased the time attribute of information, can make display message no longer is static image or scene; The 2nd, quoting of virtual reality technology provides technical foundation for realizing structure to the three-dimensional display system of the displaying of disaster view multi-angle, full-time sky.These new trends make the three dimension system that makes up Real time dynamic display disaster situation become possibility.But; Mostly present emergency system framework is the form of " database+data presentation "; This framework can not accomplish to obtain in real time disaster information, and dynamically shows, the landform that particularly demonstration is caused by geologic hazard in the geologic hazard field, the variation of landforms can't be carried out real-time update displayed.
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, can obtain disaster information in real time based on multiple agent, 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 zone is obtained remote sensing images, adopt metric space hierarchical cluster SSHC algorithm to set up multiple dimensioned disaggregated model;
The said process of setting up is: adopt the yardstick γ of image resolution ratio as the SSHC algorithm; Adopt the SSHC algorithm that remote sensing images are begun cluster calculation from the highest resolution of appointment; Regulating resolution ratio is scale parameter; To the last converge to a cluster point; Thereby form hierarchical clustering tree, promptly multiple dimensioned disaggregated model with the scale parameter convergence;
The 2nd step: each node in the hierarchical clustering tree as a classification, is set the represented atural object of each classification; Be each node setting identification, this identifies the different classes of of one side unique identification node, but also the membership between the expression node;
The 3rd step: according to hierarchical clustering tree, set up the corresponding three-dimensional model of each classification in each layer, and according to the geographic coordinate of each three-dimensional model of atural object set positions in the remote sensing images; This geographic coordinate is used for combining three-dimensional model in image, to show three-dimensional geographic pattern in the 8th step;
The 4th step: when actual the condition of a disaster situation shows, receive user instruction, user instruction comprises the atural object A that the hope of user's appointment shows, in the hierarchical clustering tree, searching the atural object A that shows with said hope is the subtree of tree root;
The 5th step: based on Agent crowd's data acquisition:
Obtain the leaf node in the said subtree; Set up one to each leaf node and gather Agent, corresponding leaf node is shared like-identified with collection Agent; Each is gathered Agent and is responsible for gathering and the data that self have like-identified; The data source of gathering the Agent image data is two types of data that are temporary in the data pool, and one type from database, and another kind of is real-time monitored data from the outside; Data in the said database and said real-time monitored data all are to have stamped the data of sign;
The 6th step: based on Agent crowd's data organization:
Set up one to each node of other except leaf node in the said subtree and organize Agent, corresponding nodes with organize Agent to share like-identified; Each organizes Agent according to sign, finds the corresponding Agent of self child node, gathers the data of all Agent that find then, as its data;
The 7th step:, will organize Agent and gather the node corresponding threedimensional model required information of data conversion that each Agent obtains among the Agent for showing this Agent representative based on the transformational relation that is provided with in advance;
The 8th step: the atural object A according to the hope of the 4th step user appointment shows, in the hierarchical clustering tree, find the pairing node of this atural object A, each three-dimensional model that utilized for the 7th step confirmed shows required information, forms the three-dimensional geographic pattern of said atural object A and shows;
The 9th step: the atural object that shows when the hope of user's appointment changes to the corresponding atural object B of a certain node in the said subtree; Then need not to carry out once more data acquisition and tissue; Each three-dimensional model that directly utilized for the 7th step confirmed shows required information, and the three-dimensional geographic pattern that carries out said atural object B shows.
The atural object that shows when the hope of user's appointment changes to atural object D, and atural object D comprises atural object A, and then in the hierarchical clustering tree, searching with said atural object D again is the new subtree of tree root; For the node of in the 5th step and the 6th step, having created Agent in the new subtree, the Agent that has created continues to use, and does not need to gather again and organize data; For the node of not creating Agent in the new subtree, then create the corresponding Agent of collection or organize Agent, and carry out corresponding data acquisition and tissue.
Preferably, this method further comprises:
Each gathers the data in the real-time monitor data of the Agent pond, and when the quantity or the numerical value of the data of finding self required collection changes, then this collection Agent carries out data collection task again;
Each organizes Agent also to monitor the Agent as its data source in real time, if find as the Agent in its data source quantity or numerical value change are arranged, then this tissue Agent carries out data organization work again;
When gathering Agent and organizing that the data of any one Agent change among the Agent; All again according to the said transformational relation that sets in advance; Agent data after changing are converted to threedimensional model show required information, and upgrade the demonstration of corresponding threedimensional model.
Wherein, preferably, said each node setting identification is a proper vector, and the dimension of proper vector begins to increase progressively successively from the tree root of hierarchical clustering tree, and every layer incremental change is 1 dimension; For father and son's node; The dimension of supposing the child node proper vector is N; Then the dimension of the proper vector of father node is N-1, and the preceding 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 used to distinguish each child node under its father node.
Preferably, in said the 5th step, data acquisition is following:
At first create and gather Agent 1; This collection Agent1 gathers the pairing data of leaf node based on being identified in the data pool; Be called the leaf node data, the pairing sign of first leaf node data of gathering as self identification, is only gathered the data with this sign;
Create again and gather Agent 2; This collection Agent 2 also gathers leaf node data according to being identified in the data pool; Whether the sign of judging the leaf node data of current collection coincides with the sign of the collection Agent that has existed; If; Then gather leaf node data again and judge, otherwise with the sign of the leaf node data of current collection as self identification; Till the collection Agent that is created can't collect the data of new kind, stop create to gather Agent, and the collection Agent that will not have a task cancels.
Preferably, in said the 6th step, the data aggregation process is following:
At first, create first and organize Agent, be designated as and organize Agent1; What this tissue Agent 1 was corresponding is the node of row second from the bottom in the subtree; Organize Agent1 that all collection Agent are sent inquiry, obtain the sign that all gather Agent, and be recorded in the statistical form; Organize Agent 1 according to sign; Find the corresponding collection Agent of all child nodes of self corresponding node; From these gather Agent, carry out data aggregation and gather, and the sign of self is added in the statistical form, the sign of the collection Agent that handled is deleted from statistical form;
Then, create second again and organize Agent, be designated as data organization Agent 2, processing procedure is identical with Agent1, until all having created organization node to all nodes of row second from the bottom in the subtree; At this moment, the quantity that identifies in the 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, what this tissue Agent 21 was corresponding is the node of countdown line 3 in the subtree, and the institute that puts down in writing in 21 pairs of statistical forms of this tissue Agent Agent in a organized way sends inquiry; Obtain the sign of Agent in a organized way, and be recorded in the statistical form; Organize Agent 21 according to sign; Find all child nodes of self corresponding node corresponding organize Agent; Organize from these and to carry out data aggregation Agent and gather, and the sign of self is added in the statistical form, the sign of handling of organizing Agent is deleted from statistical form; So far the data of having accomplished node layer third from the bottom gather;
Carry out identical establishment organize Agent to go forward side by side operation that line data gathers, the root node in handling subtree to each node layer.
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; Said multiple agent data processing unit comprises data base administration Agent, interface A gent, network data management Agent, data pool, collection Agent processing module, organizes the Agent processing module, information transforms Agent;
Said cluster cell; Be used to receive the remote sensing images in disaster to be shown zone; Adopt the yardstick γ of image resolution ratio as the SSHC algorithm; Adopt the SSHC algorithm that remote sensing images are begun cluster calculation from the highest resolution of appointment, thereby form with scale parameter convergent hierarchical clustering tree, each node in the hierarchical clustering tree is as a classification; According to the outside input, set the represented atural object of each classification and be each node setting identification; This identifies the different classes of of one side unique identification node, but also the membership between the expression node;
Interface A gent is responsible for carrying out alternately with the user; Receive user instruction; User instruction comprises the atural object A that the hope of user's appointment shows; The subtree that in the hierarchical clustering tree that cluster cell makes up, to search with said atural object A be tree root, each node in this subtree are exactly the kind of the information that will extract, and the sign of each node in this subtree is conveyed to data base administration Agent and network data management Agent respectively; And terrestrial object information to display sent to the three-dimensional model render engine;
Data base administration Agent is used for based on the sign that is received, and from said database, extracts the data with the sign that receives, and temporary in data pool;
Store space environment information and each item resource information in disaster to be shown zone in the said database;
Network data management Agent is used for based on the sign that is received, and from network, extracts the real-time monitored data with the sign that receives, and temporary in data pool;
Data in the above-mentioned database and said real-time monitored data all are to have stamped the data of sign;
Gather the Agent processing module, be used for obtaining sub-tree structure from interface A gent, obtain the leaf node in the said subtree, corresponding leaf node is shared like-identified with collection Agent; Each is gathered Agent and is responsible for from said data pool, gathering and the data that self have like-identified;
Organize the Agent processing module, be used for obtaining sub-tree structure, set up one to each node of other except leaf node in the said subtree and organize Agent from interface A gent, corresponding nodes with organize Agent to share like-identified; Each organizes Agent according to sign, finds the corresponding Agent of self child node, gathers the data of all Agent that find then, as its data;
Information transforms Agent, is a reaction equation Agent, with organizing Agent and gathering the three-dimensional model required information of data conversion for showing that this Agent representative node is corresponding that each Agent obtains among the Agent;
The three-dimensional model render engine, store with hierarchical clustering tree in the corresponding three-dimensional model of each node, and store the geographic coordinate of each three-dimensional model; When the idsplay order that receives from interface A gent; The atural object A that the hope that parses according to interface A gent shows; In the hierarchical clustering tree, find the pairing node of this atural object A, utilize information to transform the required information of each three-dimensional model of demonstration that Agent sends, in conjunction with the geographic coordinate of each three-dimensional model; Form the three-dimensional geographic pattern of said atural object A, send to graphical output device;
Graphical output device shows said three-dimensional geographic pattern.
Beneficial effect:
(1) mostly present emergency system framework is the form of " database+data presentation "; This framework can not accomplish to obtain in real time disaster information; And demonstrations dynamic, many granularities, the landform that particularly demonstration is caused by geologic hazard in the geologic hazard field, the variation of landforms can't be carried out real-time update displayed.To this problem, the present invention adds the intelligent data processing capacity module based on multiple agent between data basis and data presentation.Therefore, system framework is changed to " database+intelligent data processing+virtual reality shows ".At first adopt the SSHC algorithm that remote sensing images are carried out cluster calculation; Acquisition hierarchical clustering tree; Can carry out data acquisition, tissue flexibly, fast and realize renewal according to this tree structure, information processing rate is fast like this, thereby can handle real time data; And be converted into 3-D view and show, thereby realized dynamic demonstration.
(2) during each data organization, organize out the stalk tree in the hierarchical clustering tree, therefore under the situation that does not need data acquisition once more and tissue, can realize the image demonstration of many granularities.
(3) the present invention has adopted intelligent body to realize the intelligent data processing capacity, and each Agent has own unique perception, ability and intention; And through the common task of completion of certain modality for co-operation; Design interface of the present invention, collection, tissue and four types of basic Agent of conversion obtain data, to the data collection of classifying, and the data after gathering are made up according to level polymerization tree; Its speed is fast, and efficient is high.
(4) adopt virtual reality technology that the condition of a disaster is shown, make the participant obtain the sense organ the same, booster action is played in the formulation of emergent decision-making after the calamity with real world through Computerized three-dimensional environmental simulation technical construction virtual environment.
(5) data acquisition A gent with organize Agent that its Data Source is monitored, the real-time the condition of a disaster of obtaining changes related data, can upgrade timely if data change, thereby can realize the demonstration of the condition of a disaster change information.
Demonstration of the present invention no longer is static image or scene, the decision-maker is formulated various emergent decision-makings play important booster action.Have wide practical use and marketable value in fields such as dangerous situation simulation of burst geological hazard condition and emergency preplan simulated maneuvers, to improve burst geologic hazard emergence control level the significant contribution effect is arranged for effectively protecting people life property safety, reduction economic loss to build emergent support platform.
Description of 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 done further explain.
The invention provides a kind of emergent the condition of a disaster situation display packing based on multiple agent, this method comprises the steps:
The 1st step: disaster to be shown zone is obtained remote sensing images, adopt metric space hierarchical cluster (SSHC) algorithm to set up the multiple dimensioned disaggregated model in zone to be shown.Wherein, The process of foundation is: adopt the yardstick γ of image resolution ratio as the SSHC algorithm; Adopt the SSHC algorithm that remote sensing images are begun cluster calculation from the highest resolution of appointment, regulating resolution is scale parameter, to the last converges to a cluster point; Thereby form with scale parameter convergent hierarchical clustering tree, promptly multiple dimensioned disaggregated model.
In this step, pass rank thought from layering, the present invention adopts the SSHC algorithm to set up the information classification model with the vision dimensional variation.SSHC is a kind of cohesion type hierarchical clustering method, and this method is the laxization process with thermodynamics non-linear dynamic principle simulation human eye vision.Under the initial gauges state, each sample belongs to a classification in the sample space, and along with scale parameter changes, the mutual cluster of sample merges, and to the last converges to a cluster point, so just forms and sets with scale parameter convergent hierarchical clustering.
The principle of SSHC algorithm is: the kind of all situation information that system can show is information field U, establishes x iBe a certain type of situation information, then
Figure BDA00001771106400071
Suppose x iThe equilibrium point that changes the back trend at yardstick γ is y, then x iContribution margin to y under yardstick γ satisfies ANALOGY OF BOLTZMANN DISTRIBUTION.
According to thermodynamic principles, (classification results after the dimensional variation) entropy is maximum when system reaches equilibrium state, and free energy is minimum, shown in formula (1):
∂ F ∂ y = 0 → y = Σ x x e - γe ( x ) Σ x e - γe ( x ) - - - ( 1 )
Wherein, F is system's free energy, and e (x) is an energy function.Formula (1) is derived, has:
y → y + Σ x ( x - y ) e - γe ( x ) Σ x e - γe ( x ) - - - ( 2 )
Formula (2) explains that under the certain situation of yardstick γ x can converge to a fixed value y through 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 the SSHC model, what time following all element α that can show in the system, satisfy:
1, under initial gauges,
Figure BDA00001771106400083
2, when yardstick changes,
Figure BDA00001771106400084
3, when yardstick is maximum,
Figure BDA00001771106400085
wherein Y is final convergence result.
Therefore, α, x, y can adopt the set membership in the tree construction to represent, after accomplishing cluster at different scale, just can obtain the 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.
When adopting the SSHC algorithm to remote sensing images so, adopt the yardstick γ of image resolution ratio, the corresponding sighting distance of each yardstick as the SSHC algorithm.Adopt the SSHC algorithm that remote sensing images are begun cluster calculation from the highest resolution of appointment, this best result distinguishes to be that lowest scale is artificial appointment, and relevant (it is thus clear that atural object is meant ground object with hoping the most fine-grained atural object that obtains for this; Street for example, crossroad etc.), along with scale parameter changes; The mutual cluster of sample merges, and to the last converges to a cluster point, and this cluster point is the highest yardstick; It is the maximum atural object of granularity in the image, for example whole mountain region; Thereby form with scale parameter convergent hierarchical clustering tree, promptly multiple dimensioned disaggregated model through polymerization repeatedly.
In hierarchical clustering tree, the highest yardstick and lowest scale are root node and the leaf nodes of hierarchical clustering tree, the yardstick of each layer correspondence in the hierarchical clustering tree, and the node in every layer is represented the cluster centre of cluster formation under this layer yardstick.The scale span of cluster process can be confirmed by artificial, branch thin more, and the level that can show during demonstration is just many more.
The 2nd goes on foot: each node during hierarchical clustering is set is as a classification; Set the represented atural object of each classification; And set proper vector for each node, this proper vector is used for the membership between the identification nodes, thereby can know which kind of node belongs in whole hierarchical clustering tree.
Aforementioned the 1st step only is to carry out cluster to remote sensing images, obtain the hierarchical clustering tree, but each cluster centre in each layer does not still have concrete implication.Need manual work to give a concrete characters of ground object below 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, and the child node of node layer is not drawn in some; In fact the number of plies of descendants's node of node layer is identical in all, because cluster is from bottom to top.So in this step; Need each node in this clustering tree as a classification, though there is membership between the node of levels, owing to the difference of yardstick; Therefore regard them as different classes; Set the represented atural object of each classification, when setting, notice that the atural object of father and son's node also is set membership.For example, the child node of x2 comprises x21, x22, x23, and x2 is set at the residential block, and x21, x22, x23 are set at residential quarters, commercial block and factory district respectively.
For the ease of follow-up data qualification and tissue; In this step, also need be each node setting identification, this identifies the different classes of of one side unique identification node; But also can represent the membership between the node, thereby can know the position of node in whole hierarchical clustering tree.
In reality, vector is a kind of sign of using always, and its design is more flexible, and is convenient to computer Recognition, and occupies little space.In the embodiment shown in fig. 1, adopt vector, be called proper vector as said sign.Proper vector is a multidimensional, and its dimension has been represented node place level, and the dimension of proper vector begins 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 the child node proper vector is N; The dimension of father node proper vector is N-1 so, and then the preceding 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 used to distinguish 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).
It is thus clear that the setting of this proper vector can identify the membership between the node, thereby can know the position of node in whole yardstick disaggregated model.
The 3rd step: to each node in the 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 each three-dimensional model of atural object set positions in the remote sensing images; This geographic coordinate is used for combining three-dimensional model in image, to show three-dimensional geographic pattern in the 8th step.
Still be example, set up the three-dimensional model of residential block, set up the three-dimensional model of residential quarters, commercial block, factory district for node x21, x22, x23 respectively for node x2 with Fig. 1.Defined the information that shows that this three-dimensional model is required in this three-dimensional model, these information are follow-up by gathering Agent and organizing Agent to gather and tissue, obtain through transforming then.
Three-dimensional modeling need be used the landform source data, and the landform source data is the digital elevation data, and its acquisition methods has following several kinds: 1) adopt geodesic method directly to measure elevation from landform; 2) utilize the photogrammetric measurement photo, adopt digital elevation to judge that appearance reads elevation from the photo of two correspondences; 3) utilize the 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 U.S. image map office (NIMA), and converts the special-purpose DED data layout of Creator to and carry out the dimensional topography modeling.
The 4th step: when actual the condition of a disaster situation shows, receive user command, user instruction comprises the atural object A that the hope of user's appointment shows, in the hierarchical clustering tree, searching the atural object A that shows with hope is the subtree of tree root.
For example, the user hopes to show residential block x2, and then in the hierarchical clustering tree, searching with x2 is the subtree of 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.
Descendants's node described in this paper is meant with father node has all child nodes of membership, child node of child node or the like, and child node just is meant the child node that direct set membership is arranged with father node, does not comprise the interlayer child node.
The 5th step: based on Agent crowd's data acquisition:
Obtain the node of the bottom in the 4th subtree that finds of step, i.e. leaf node.Set up one to each leaf node and gather Agent, corresponding leaf node is shared like-identified with collection Agent; Each is gathered Agent and is responsible for gathering and the data that self have like-identified; The data source of gathering the Agent image data comprise be temporary in the data pool from the data in the database, and from the real-time monitored data of outside; Data in the said database and said real-time monitored data all are to have stamped the data of sign.
Wherein, Agent is the English of intelligent body, and Agent has independence, communication property, reactivity and cooperative functional module, and multi-agent system (MAS) cooperatively interacts based on the subtask that several Agent carry out, and accomplishes its predetermined general assignment.The present invention adopts the acquisition module of Agent as this step, can improve data acquisition efficiency, the data acquisition of each module completion self type.
Data source among the present invention comprises database, real-time monitored data.Database is responsible for record space environmental information and each item resource information etc., and these all are that three-dimensional model shows required information, and the content in the database can be upgraded according to actual conditions.The real-time monitored data refer to that the various information that in network environment, obtains comprises data, satellite remote sensing images, the image of unmanned plane near-earth shooting and all kinds of real-time information that the process Flame Image Process draws of various kinds of sensors or the like, and this category information also is that three-dimensional model shows required information.This two category information has all carried out adding the processing of sign in advance, gathers Agent and only gathers the data that those have sign.
In data acquisition:
At first; Create first and gather Agent---gather Agent1; This collection Agent 1 gathers the pairing data of leaf node according to being identified in the data pool; Be called the leaf node data; The pairing sign of first leaf node data of gathering as self identification, is only gathered the data with this sign;
Then; Create two and gather Agent---gather Agent 2; This collection Agent 2 also gathers leaf node data according to being identified in the data pool; Whether the sign of judging the leaf node data of current collection coincides with the sign of the collection Agent that has existed; If; Then gather leaf node data again and judge, otherwise with the sign of the leaf node data of current collection as self identification;
Constantly create new collection Agent, till the collection Agent that is created can't collect the data of new kind, stop to create and gather Agent, and the collection Agent that will not have a task cancels.Like this, with the data category in the data pool separately, belong to different collection Agent respectively and be responsible for.
The 6th step: based on Agent crowd's data organization:
Set up one to each node of other except leaf node in the said subtree and organize Agent, corresponding nodes with organize Agent to share like-identified; Each organizes Agent according to sign; Find self all corresponding child node 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); The data that gather the Agent that finds then are as its data.The data sink of organizing Agent always from bottom to top, the Agent that organizes by lower floor gathers earlier, the Agent that organizes by the upper strata gathers again.
When said when being designated aforesaid proper vector; Suppose that organizing the proper vector of Agent is the N dimension; Then to search proper vector be N+1 dimension to this tissue Agent; And preceding N dimensional feature vector is with the vectorial identical collection Agent of unique characteristics or organize Agent, gathers the data of the Agent that finds then, as its data.
Still be example with Fig. 1, the Agent that organizes that x23 is corresponding gathers the data of the collection Agent of x231 and x232 correspondence, and the Agent that organizes that x2 is corresponding gathers the corresponding data of organizing Agent of x21, x22 and x23.
In the data organization process:
At first; Create first and organize Agent---organize Agent 1, what this tissue Agent 1 was corresponding is the node of row second from the bottom in the subtree, organizes 1 couple of all collection Agent of Agent to send inquiry; Obtain the sign that all gather Agent, and be recorded in the statistical form.Organize Agent 1 according to sign; Find the corresponding collection Agent of all child nodes of self corresponding node; From these gather Agent, carry out data aggregation and gather, and the sign of self is added in the statistical form, the sign of the collection Agent that handled is deleted from statistical form.If be designated proper vector, then find proper vector than unique characteristics vector length 1, and preceding N-1 dimensional feature vector and the identical proper vector of unique characteristics vector, and find corresponding collection Agent, gather the Agent from these and carry out data aggregation, and gather.
Then, creating second again and organize Agent---data organization Agent 2, and processing procedure is identical with Agent 1, until all having created organization node to all nodes of row second from the bottom in the subtree; At this moment, the quantity that identifies in the 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, what this tissue Agent 21 was corresponding is the node of countdown line 3 in the subtree, and the institute that puts down in writing in 21 pairs of statistical forms of this tissue Agent Agent in a organized way sends inquiry; Obtain the sign of Agent in a organized way, and be recorded in the statistical form.Organize Agent 21 according to sign; Find all child nodes of self corresponding node corresponding organize Agent; Organize from these and to carry out data aggregation Agent and gather, and the sign of self is added in the statistical form, the sign of handling of organizing Agent is deleted from statistical form; So far the data of having accomplished node layer third from the bottom gather;
Carry out identical establishment organize Agent to go forward side by side operation that line data gathers, the root node in handling subtree to each node layer.
The 7th step:, will organize Agent and the data conversion of gathering each Agent acquisition among the Agent to show required information for the corresponding threedimensional model of node that shows this Agent representative based on the transformational relation that is provided with in advance.
The 8th step: the atural object A according to the hope of the 4th step user appointment shows, in the hierarchical clustering tree, find the pairing node of this atural object A, each three-dimensional model that utilized for the 7th step confirmed shows required information, the three-dimensional geographic pattern that carries out said atural object A shows.
The 9th step: the atural object that shows when the hope of user's appointment changes to the corresponding atural object B of a certain node in the said subtree; Then need not to carry out once more data acquisition and tissue; Each three-dimensional model that directly utilized for the 7th step confirmed shows required information, and the three-dimensional geographic pattern that carries out said atural object B shows.
Thus it is clear that, after the subtree that to atural object A is root node is accomplished know clearly data acquisition and tissue, can show atural object A and more fine-grained atural object thereof, and not need to carry out again data acquisition and tissue.Thereby realized that fast data is handled and demonstration.
When needs show atural object C, and atural object C do not comprise atural object A, then confirms again new subtree promptly to begin again the operation of execution in step 4 ~ 8 from step 4.
When needs show the atural object D of coarsegrain more, and atural object D comprises atural object A, can confirm new subtree equally again, promptly begins again the operation of execution in step 4 ~ 8 from step 4.But in order to reduce the processing time, preferably, in the hierarchical clustering tree, searching with said atural object D again is the new subtree of tree root; For the node of in the 5th step and the 6th step, having created Agent in the new subtree; The Agent that creates can continue to use, and does not need to gather again and organize data, for the part of not creating Agent in the new subtree; Then create Agent, and carry out corresponding data acquisition and tissue.The process of data acquisition and tissue is identical with described mode of the 6th step with the 5th step.
Each gathers also data in the monitor data pond in real time of Agent, when finding the data variation of self required collection, and number change for example, numerical value change, then this collection Agent carries out data collection task again; In like manner, each organizes Agent also to monitor the Agent as its data source in real time, if find as the Agent in its data source quantity or numerical value change are arranged, then this tissue Agent carries out data organization work again; When collection Agent changes with the data of organizing any Agent among the Agent, all again according to the transformational relation that is provided with in advance, convert three-dimensional model into 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 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 A gent, network data management Agent, data pool, collection Agent processing module, organizes Agent processing module and information to transform Agent.
Function in the face of each module is described in detail down.
Cluster cell; Be used to receive the remote sensing images in disaster to be shown zone; Adopt the yardstick γ of image resolution ratio as the SSHC algorithm; Adopt the SSHC algorithm that remote sensing images are begun cluster calculation from the highest resolution of appointment, thereby form with scale parameter convergent hierarchical clustering tree, each node in the hierarchical clustering tree is as a classification; According to the outside input, set the represented atural object of each classification and be each node setting identification; This identifies the different classes of of one side unique identification node, but also the membership between the expression node.This sign can adopt aforesaid proper vector.
Interface A gent is responsible for carrying out alternately with the user; Receive user instruction; User instruction comprises the atural object A that the hope of user's appointment shows; The subtree that in the hierarchical clustering tree that cluster cell makes up, to search with said atural object A be tree root, each node in this subtree are exactly the kind of the information that will extract, and the sign of each node in this subtree is conveyed to data base administration Agent and network data management Agent respectively; And terrestrial object information to display sent to the three-dimensional model render engine.
Data base administration Agent is used for based on the sign that is received, and from said database, extracts the data with the sign that receives, and temporary in data pool.
Network data management Agent is used for based on the sign that is received, and from network, extracts the real-time monitored data with the sign that receives, and temporary in data pool.
Store space environment information and each item resource information in disaster to be shown zone in the said database.
Data in the above-mentioned database and said real-time monitored data all are to have stamped the data of sign.
Gather the Agent processing module, be used for obtaining sub-tree structure from interface A gent, obtain the leaf node in the said subtree, corresponding leaf node is shared like-identified with collection Agent; Each is gathered Agent and is responsible for from said data pool, gathering and the data that self have like-identified.
In data acquisition, at first create and gather Agent 1, this Agent 1 carries out data acquisition according to proper vector, is as the criterion with its first data class of being gathered, only gathers the data of this kind; At this moment, create Agent 2 again, carry out data acquisition, and Agent 1 is inquired, both gather same type of data its, are then to change one type of data, not, then continue to gather this category information; Can't collect until the Agent that is created till the data of new kind, stop to create Agent, and the Agent that will not have a task cancels.Like this, with the data category in the data pool separately, belong to different collection Agent respectively and be responsible for.
Organize the Agent processing module, be used for from the interface that agent obtains sub-tree structure, set up one to each node of other except leaf node in the said subtree and organize Agent, corresponding nodes with organize Agent to share like-identified; Each organizes Agent according to sign, finds the corresponding Agent of self child node, gathers the data of all Agent that find then, as its data.
In the data organization process; Same elder generation organizes Agent1 by establishment, and 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 the statistical form.According to the proper vector of putting down in writing in this statistical form, find proper vector than unique characteristics vector length 1, and preceding N-1 dimensional feature vector and the identical proper vector of unique characteristics vector, and find corresponding Agent, from these Agent, carry out data aggregation, and gather.Then that it is collected data class characteristic of correspondence vector is deleted from statistical form.System creates data organization Agent 2 more afterwards, and processing procedure is identical with Agent 1.In statistical form till the no proper vector.
Information transforms Agent, is a reaction equation Agent, with organizing Agent and gathering the three-dimensional model required information of data conversion for showing that this Agent representative node is corresponding that each Agent obtains among the Agent.
The three-dimensional model render engine, store with hierarchical clustering tree in the corresponding three-dimensional model of each node, and store the geographic coordinate of each three-dimensional model; When the idsplay order that receives from interface agent; The atural object A that the hope that parses according to interface agent shows; In the hierarchical clustering tree, find the pairing node of this atural object A, utilize information to transform the required information of each three-dimensional model of demonstration that Agent sends, in conjunction with the geographic coordinate of each three-dimensional model; Form the three-dimensional geographic pattern of said atural object A, send to graphical output device.The Terrain tool box that this three-dimensional model render engine can adopt the Creator modeling software to provide makes ground model, plays up the virtual reality Presentation Function that the bag MultiGen Vega 3.7.1 that develops software realizes system through calling based on the three-dimensional picture of OpenGL.
Graphical output device shows said three-dimensional geographic pattern.
After interface A gent receives user instruction once more; The atural object that shows when the hope of user instruction appointment changes to the corresponding atural object B of a certain node in the said subtree; Then interface A gent is to passing on network data management Agent and data base administration Agent to pass on fresh information; Directly send instruction and give the 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.
After interface A gent received user instruction once more, the atural object that shows when the hope of user's appointment changed to atural object D, and atural object D comprises atural object A, and then in the hierarchical clustering tree, searching with said atural object D again is the new subtree of tree root; More said subtree and said new subtree for the new node that increases in the new subtree, convey to data base administration Agent and network data management Agent respectively with the sign of new node, are that new node is collected data by these two Agent, are put in the data pool; And send instruction and give the 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 the Agent processing module and organize the Agent processing module according to new subtree, for the node of having created Agent in the new subtree, the Agent that has created continues to use, and does not need to gather again and organize data; For the node of not creating Agent in the new subtree, then create the corresponding Agent of collection or organize Agent, and carry out corresponding data acquisition and tissue.
Preferably, each gathers the data in the real-time monitor data of the Agent pond, and when the quantity or the numerical value of the data of finding self required collection changes, then this collection Agent carries out data collection task again;
Simultaneously, each organizes Agent also to monitor the Agent as its data source in real time, if find as the Agent in its data source quantity or numerical value change are arranged, then this tissue Agent carries out data organization work again;
So; When collection Agent changes with the data of organizing any Agent among the Agent; All notifying the Agent data-switching after the three-dimensional model render engine will change again is that three-dimensional model shows required information, and upgrades three-dimensional geographic pattern, sends to graphical output device.
Visible by 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 different Agent of each function to carry out a series of information processing, and finally adopt virtual reality technology to carry out dynamically, overall situation shows fast.Multiple agent technology and virtual reality technology realization combining intelligent data are handled and quick Presentation Function.Each Agent has own unique perception; Ability and intention; And through the common task of completion of certain modality for co-operation, and virtual reality technology is meant through Computerized three-dimensional environmental simulation technical construction virtual environment and makes the participant obtain the sense organ the same with real world.The present invention relates to interface, collection, tissue and four types of basic Agent of conversion, realized the process from data to the display message through the cooperation between them.
This shows, the present invention is directed to prior art problems, between data basis and data presentation, add intelligent data processing capacity module based on multiple agent.Therefore, system framework is changed to " database+intelligent data processing+virtual reality shows ".The function that intelligent data is handled is to realize from mass data information intelligence, extract related data fast, and transforms into directly the information that can be shown by VR-Platform.
In sum, more than being merely preferred embodiment of the present invention, is not to be used to limit protection scope of the present invention.All within spirit of the present invention and principle, any modification of being done, be equal to replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (10)

1.一种基于多智能体Agent的应急灾情态势显示方法,其特征在于,包括:1. A multi-agent agent-based emergency disaster situation display method, characterized in that, comprising: 第1步:对待显示灾害区域获取遥感图像,采用尺度空间分层聚类SSHC算法建立多尺度分类模型;Step 1: Obtain remote sensing images for the disaster area to be displayed, and use the scale-space hierarchical clustering SSHC algorithm to establish a multi-scale classification model; 所述建立过程为:采用图像分辨率作为SSHC算法的尺度γ,采用SSHC算法对遥感图像从指定的最高分辨率开始聚类计算,调节分辨率即尺度参数,直到最后收敛为一个聚类点,从而形成随尺度参数收敛的层次聚类树,即多尺度分类模型;The establishment process is: using the image resolution as the scale γ of the SSHC algorithm, using the SSHC algorithm to cluster the remote sensing image from the specified highest resolution, adjusting the resolution, that is, the scale parameter, until finally converging to a clustering point, Thus forming a hierarchical clustering tree that converges with the scale parameters, that is, a multi-scale classification model; 第2步:将层次聚类树中的每个节点作为一个类别,设定每个类别所表示的地物;为每个节点设定标识,该标识一方面唯一标识节点的不同类别,而且还表示节点之间的隶属关系;Step 2: Take each node in the hierarchical clustering tree as a category, and set the features represented by each category; set an identifier for each node, which uniquely identifies different categories of nodes on the one hand, and also Represents the affiliation relationship between nodes; 第3步:根据层次聚类树,建立每个层中每个类别对应的三维模型,并根据遥感图像中的地物位置设定每个三维模型的地理坐标;该地理坐标用于在第8步中结合三维模型在图像中显示三维地理图像;Step 3: According to the hierarchical clustering tree, establish the 3D model corresponding to each category in each layer, and set the geographic coordinates of each 3D model according to the location of the ground objects in the remote sensing image; the geographic coordinates are used in the 8th step Combined with the 3D model in the step to display the 3D geographic image in the image; 第4步:实际灾情态势显示时,接收用户指令,用户指令包括用户指定的希望显示的地物A,在层次聚类树中查找以所述希望显示的地物A为树根的子树;Step 4: When the actual disaster situation is displayed, receive a user instruction, the user instruction includes the feature A desired to be displayed specified by the user, and search for a subtree whose root is the feature A desired to be displayed in the hierarchical clustering tree; 第5步:基于Agent群的数据采集:Step 5: Data collection based on Agent group: 获取所述子树中的叶子节点;针对每个叶子节点建立一个采集Agent,对应的叶子节点和采集Agent共享相同标识;每个采集Agent负责采集与自身具有相同标识的数据;采集Agent采集数据的数据源为暂存于数据池中的两类数据,一类来自数据库,另一类为来自外部的实时观测数据;所述数据库中的数据和所述实时观测数据均是已经打上标识的数据;Obtain the leaf nodes in the subtree; set up a collection Agent for each leaf node, and the corresponding leaf node and collection Agent share the same identification; each collection Agent is responsible for collecting data with the same identification as itself; collection Agent collection data The data source is two types of data temporarily stored in the data pool, one is from the database, and the other is real-time observation data from the outside; the data in the database and the real-time observation data are all marked data; 第6步:基于Agent群的数据组织:Step 6: Data organization based on Agent group: 针对所述子树中除了叶子节点之外的其他每个节点建立一个组织Agent,对应的节点和组织Agent共享相同标识;每个组织Agent根据标识,找到自身子节点对应的Agent,然后汇总找到的所有Agent的数据,作为自身数据;Establish an organization Agent for each node except the leaf node in the subtree, and the corresponding node and the organization Agent share the same identifier; each organization Agent finds the Agent corresponding to its own child node according to the identifier, and then summarizes the found All Agent data, as its own data; 第7步:根据预先设置的转换关系,将组织Agent和采集Agent中每个Agent获得的数据转化为显示该Agent所代表的节点对应的三维模型所需的信息;Step 7: According to the pre-set conversion relationship, transform the data obtained by each Agent in the organization Agent and the collection Agent into the information required to display the three-dimensional model corresponding to the node represented by the Agent; 第8步:根据第4步用户指定的希望显示的地物A,在层次聚类树中找到该地物A所对应的节点,利用第7步确定的各三维模型显示所需的信息,形成所述地物A的三维地理图像并显示;Step 8: According to the feature A that the user specifies to display in step 4, find the node corresponding to the feature A in the hierarchical clustering tree, use the 3D models determined in step 7 to display the required information, and form and displaying the three-dimensional geographic image of the feature A; 第9步:当用户指定的希望显示的地物变更为所述子树中某一节点对应的地物B,则无需再次进行数据采集和组织,直接利用第7步确定的各三维模型显示所需的信息,进行所述地物B的三维地理图像显示。Step 9: When the user-designated feature to be displayed is changed to feature B corresponding to a certain node in the subtree, there is no need to collect and organize data again, and directly use the 3D models determined in step 7 to display all The required information is displayed on the three-dimensional geographic image of the feature B. 2.如权利要求1所述的方法,其特征在于,该方法进一步包括:2. The method of claim 1, further comprising: 当用户指定的希望显示的地物变更为地物D,且地物D包含地物A,则重新在层次聚类树中查找以所述地物D为树根的新子树;对于新子树中已经在第5步和第6步中创建了Agent的节点,已创建的Agent继续使用,不需要重新采集和组织数据;对于新子树中没有创建Agent的节点,则创建相应的采集Agent或组织Agent,并进行相应的数据采集和组织。When the feature that the user wants to display is changed to feature D, and feature D contains feature A, then search for a new subtree with the feature D as the root in the hierarchical clustering tree; for the new subtree For nodes in the tree that have created Agents in Steps 5 and 6, the created Agents continue to be used without re-collecting and organizing data; for nodes that have not created Agents in the new subtree, create corresponding collection Agents Or organize Agent, and carry out corresponding data collection and organization. 3.如权利要求1或2所述的方法,其特征在于,该方法进一步包括:3. The method according to claim 1 or 2, characterized in that the method further comprises: 各个采集Agent实时监控数据池中的数据,当发现自身所需采集的数据的数量或数值发生变化,则该采集Agent重新进行数据采集工作;Each acquisition agent monitors the data in the data pool in real time, and when it finds that the quantity or value of the data it needs to collect changes, the acquisition agent restarts the data acquisition work; 各个组织Agent也实时监控作为自身数据来源的Agent,如果发现作为自身数据来源的Agent有数量或数值变化,则该组织Agent重新进行数据组织工作;Each organization Agent also monitors the Agent as its own data source in real time. If it finds that the number or value of the Agent as its own data source has changed, the organization Agent will re-organize the data; 当采集Agent和组织Agent中任意一个Agent的数据发生变化时,均重新根据所述预先设置的转换关系,将变化后的Agent数据转换为三维模型显示所需的信息,并更新相应三维模型的显示。When the data of any Agent in the collection Agent and the organization Agent changes, the changed Agent data is converted into the information required for the three-dimensional model display according to the preset conversion relationship again, and the display of the corresponding three-dimensional model is updated. . 4.如权利要求1所述的方法,其特征在于,所述每个节点设定标识为特征向量,特征向量的维数从层次聚类树的树根开始依次递增,每层的递增量为1维;对于父子节点,假设子节点特征向量的维数为N,则父节点的特征向量的维数为N-1,子节点的前N-1维向量与其父节点的特征向量一致,子节点的第N维向量用于区别在其父节点下的各子节点。4. method as claimed in claim 1, is characterized in that, described each node setting mark is feature vector, and the dimension of feature vector increases successively from the tree root of hierarchical clustering tree, and the increment of every layer is 1 dimension; for a parent-child node, assuming that the dimension of the feature vector of the child node is N, the dimension of the feature vector of the parent node is N-1, and the first N-1 dimension vector of the child node is consistent with the feature vector of its parent node, and the child node The Nth dimension vector of a node is used to distinguish each child node under its parent node. 5.如权利要求1所述的方法,其特征在于,在所述第5步中,首先创建采集Agent 1,该采集Agent 1根据标识在数据池中采集一个叶子节点所对应的数据,称为叶子节点数据,将采集的第一个叶子节点数据所对应的标识作为自身标识,只采集具有该标识的数据;5. the method for claim 1 is characterized in that, in described 5th step, at first create and gather Agent 1, this gathers Agent 1 and collects the corresponding data of a leaf node in data pool according to mark, is called For the leaf node data, the identifier corresponding to the collected first leaf node data is used as its own identifier, and only the data with this identifier is collected; 再创建采集Agent 2,该采集Agent 2也根据标识在数据池中采集一个叶子节点数据,判断当前采集的叶子节点数据的标识是否与已经存在的采集Agent的标识相重合,如果是,则再采集一个叶子节点数据并进行判断,否则将当前采集的叶子节点数据的标识作为自身标识;直至所创建的采集Agent无法采集到新的种类的数据为止,停止创建采集Agent,并将无任务的采集Agent撤销。Then create collection Agent 2, the collection Agent 2 also collects a leaf node data in the data pool according to the logo, and judges whether the logo of the currently collected leaf node data coincides with the logo of the existing collection Agent, and if so, collects again A leaf node data and make a judgment, otherwise, the identification of the currently collected leaf node data will be used as its own identification; until the created collection Agent cannot collect new types of data, stop creating the collection Agent, and the collection Agent without tasks undo. 6.如权利要求1所述的方法,其特征在于,在所述第6步中,首先,创建第一个组织Agent,记为组织Agent1,该组织Agent1对应的是子树中倒数第二行的节点,组织Agent1对所有的采集Agent发出询问,获得所有采集Agent的标识,并记录在统计表中;组织Agent1根据标识,找到自身对应节点的所有子节点对应的采集Agent,从这些采集Agent中进行数据收集并汇总,并且将自身的标识添加到统计表中,将处理过的采集Agent的标识从统计表中删除;6. The method according to claim 1, characterized in that, in the sixth step, firstly, create the first organization Agent, denoted as organization Agent1, and this organization Agent1 corresponds to the penultimate row in the subtree The organization Agent1 sends inquiries to all collection Agents, obtains the identification of all collection Agents, and records them in the statistical table; organizes Agent1 to find the collection Agents corresponding to all sub-nodes of its corresponding node according to the identification, and collects from these collection Agents Carry out data collection and summary, and add its own identification to the statistical table, and delete the processed collection Agent's identification from the statistical table; 然后,再创建第二个组织Agent,记为数据组织Agent 2,处理过程与Agent1相同,直至针对子树中倒数第二行的所有节点均创建了组织节点;此时,统计表中标识的数量与倒数第二行的节点数量相同;Then, create a second organization Agent, denoted as data organization Agent 2, the process is the same as Agent1, until organization nodes are created for all nodes in the second-to-last row in the subtree; at this time, the number identified in the statistics table The same number of nodes as the penultimate row; 此后,再创建一个组织Agent,记为组织Agent 21,该组织Agent 21对应的是子树中倒数第三行的节点,该组织Agent 21对统计表中记载的所有组织Agent发出询问,获得所有组织Agent的标识,并记录在统计表中;组织Agent 21根据标识,找到自身对应节点的所有子节点对应的组织Agent,从这些组织Agent中进行数据收集并汇总,并且将自身的标识添加到统计表中,将处理过的组织Agent的标识从统计表中删除;至此完成了倒数第三层节点的数据汇总;Thereafter, another organization Agent is created, which is recorded as organization Agent 21. This organization Agent 21 corresponds to the node in the penultimate row of the subtree. This organization Agent 21 sends an inquiry to all organization Agents recorded in the statistics table to obtain Agent's identification, and record in the statistics table; Organization Agent 21 finds the organization Agent corresponding to all child nodes of its corresponding node according to the identification, collects and summarizes data from these organization Agents, and adds its own identification to the statistics table In the process, delete the identity of the processed organization Agent from the statistical table; so far, the data summary of the third-to-last layer node has been completed; 针对每一层节点执行相同的创建组织Agent并进行数据汇总的操作,直到处理完子树中的根节点。For each layer of nodes, perform the same operation of creating an organization Agent and performing data aggregation until the root node in the subtree is processed. 7.一种基于多智能体的应急灾情态势显示系统,其特征在于,该系统包括聚类单元、数据库、多智能体数据处理单元、三维模型渲染引擎和图形输出设备;所述多智能体数据处理单元包括数据库管理Agent、界面Agent、网络数据管理Agent、数据池、采集Agent处理模块、组织Agent处理模块、信息转化Agent;7. A multi-agent emergency disaster situation display system is characterized in that the system includes a clustering unit, a database, a multi-agent data processing unit, a three-dimensional model rendering engine and a graphic output device; the multi-agent data The processing unit includes database management Agent, interface Agent, network data management Agent, data pool, collection Agent processing module, organization Agent processing module, and information conversion Agent; 所述聚类单元,用于接收待显示灾害区域的遥感图像,采用图像分辨率作为SSHC算法的尺度γ,采用SSHC算法对遥感图像从指定的最高分辨率开始聚类计算,从而形成随尺度参数收敛的层次聚类树,层次聚类树中的每个节点作为一个类别;根据外部输入,设定每个类别所表示的地物以及为每个节点设定标识;该标识一方面唯一标识节点的不同类别,而且还表示节点之间的隶属关系;The clustering unit is used to receive the remote sensing image of the disaster area to be displayed, using the image resolution as the scale γ of the SSHC algorithm, and using the SSHC algorithm to cluster and calculate the remote sensing image from the specified highest resolution, thereby forming a scale parameter Convergent hierarchical clustering tree, each node in the hierarchical clustering tree is regarded as a category; according to the external input, set the features represented by each category and set an identifier for each node; on the one hand, the identifier uniquely identifies the node different categories of , and also represents the membership relationship between nodes; 界面Agent负责与用户进行交互,接收用户指令,用户指令包括用户指定的希望显示的地物A,在聚类单元构建的层次聚类树中查找以所述地物A为树根的子树,该子树中的各节点就是要提取的信息的种类,将该子树中各节点的标识分别传达给数据库管理Agent和网络数据管理Agent;并将所要显示的地物信息发送给三维模型渲染引擎;The interface Agent is responsible for interacting with the user, receiving user instructions, the user instructions include the feature A specified by the user to be displayed, and searching for the subtree with the feature A as the root in the hierarchical clustering tree constructed by the clustering unit, Each node in the subtree is the type of information to be extracted, and the identification of each node in the subtree is conveyed to the database management agent and the network data management agent respectively; and the feature information to be displayed is sent to the 3D model rendering engine ; 数据库管理Agent,用于根据所接收的标识,从所述数据库中提取具有所接收标识的数据,并暂存到数据池中;The database management agent is used to extract the data with the received identifier from the database according to the received identifier, and temporarily store it in the data pool; 所述数据库中存储有待显示灾害区域的空间环境信息和各项资源信息;The database stores the spatial environment information and various resource information of the disaster area to be displayed; 网络数据管理Agent,用于根据所接收的标识,从网络中提取具有所接收标识的实时观测数据,并暂存到数据池中;The network data management Agent is used to extract real-time observation data with the received identifier from the network according to the received identifier, and temporarily store it in the data pool; 上述数据库中的数据和所述实时观测数据均是已经打上标识的数据;The data in the above database and the real-time observation data are all marked data; 采集Agent处理模块,用于从界面Agent中获取子树结构,获取所述子树中的叶子节点,对应的叶子节点和采集Agent共享相同标识;每个采集Agent负责从所述数据池中采集与自身具有相同标识的数据;Collect Agent processing module, be used for obtaining subtree structure from interface Agent, obtain the leaf node in described subtree, corresponding leaf node and collect Agent share the same identification; Each collect Agent is responsible for collecting and data that itself has the same identity; 组织Agent处理模块,用于从界面Agent中获取子树结构,针对所述子树中除了叶子节点之外的其他每个节点建立一个组织Agent,对应的节点和组织Agent共享相同标识;每个组织Agent根据标识,找到自身子节点对应的Agent,然后汇总找到的所有Agent的数据,作为自身数据;The organization Agent processing module is used to obtain the subtree structure from the interface Agent, and establish an organization Agent for each node in the subtree except the leaf node, and the corresponding node and the organization Agent share the same identification; each organization The agent finds the agent corresponding to its own child node according to the identification, and then summarizes the data of all the found agents as its own data; 信息转化Agent,是一个反应式Agent,将组织Agent和采集Agent中每个Agent获得的数据转化为显示该Agent所代表节点对应的三维模型所需的信息;The information conversion agent is a reactive agent, which converts the data obtained by each agent in the organization agent and collection agent into the information required to display the three-dimensional model corresponding to the node represented by the agent; 三维模型渲染引擎,存储有与层次聚类树中每个节点对应的三维模型,并且存储有各三维模型的地理坐标;当接收到来自界面Agent的显示指令时,根据界面Agent解析出的希望显示的地物A,在层次聚类树中找到该地物A所对应的节点,利用信息转化Agent发来的显示各三维模型所需的信息,结合各三维模型的地理坐标,形成所述地物A的三维地理图像,发送给图形输出设备;The 3D model rendering engine stores the 3D model corresponding to each node in the hierarchical clustering tree, and stores the geographic coordinates of each 3D model; when receiving a display command from the interface Agent, it will display Find the corresponding node of the feature A in the hierarchical clustering tree, use the information needed to display each 3D model sent by the information conversion agent, and combine the geographic coordinates of each 3D model to form the feature The three-dimensional geographic image of A is sent to the graphic output device; 图形输出设备,显示所述三维地理图像。A graphics output device displays the three-dimensional geographic image. 8.如权利要求7所述的系统,其特征在于,界面Agent再次接收用户指令,当用户指令指定的希望显示的地物变更为所述子树中某一节点对应的地物B,则界面Agent不向传达网络数据管理Agent和数据库管理Agent传达新信息,直接发送指令给三维模型渲染引擎,通知三维模型渲染引擎形成地物B的三维地理图像,发送给图形输出设备。8. The system according to claim 7, wherein the interface Agent receives the user instruction again, and when the feature desired to be displayed specified by the user instruction is changed to the feature B corresponding to a certain node in the subtree, the interface The Agent does not convey new information to the Network Data Management Agent and the Database Management Agent, but directly sends instructions to the 3D model rendering engine, instructing the 3D model rendering engine to form a 3D geographic image of feature B and send it to the graphics output device. 9.如权利要求7或8所述的系统,其特征在于,界面Agent再次接收用户指令,当用户指定的希望显示的地物变更为地物D,且地物D包含地物A,则重新在层次聚类树中查找以所述地物D为树根的新子树;比较所述子树和所述新子树,对于新子树中增加的新节点,将新节点的标识分别传达给数据库管理Agent和网络数据管理Agent;并且发送指令给三维模型渲染引擎,通知三维模型渲染引擎形成地物D的三维地理图像,发送给图形输出设备;9. The system according to claim 7 or 8, wherein the interface Agent receives user instructions again, and when the user-designated feature to be displayed is changed to feature D, and feature D includes feature A, then Search for a new subtree with the feature D as the root in the hierarchical clustering tree; compare the subtree with the new subtree, and for the new nodes added in the new subtree, convey the identifiers of the new nodes respectively To the database management Agent and the network data management Agent; and sending instructions to the 3D model rendering engine, instructing the 3D model rendering engine to form a 3D geographical image of the feature D, and sending it to the graphics output device; 采集Agent处理模块和组织Agent处理模块根据新子树,对于新子树中已经创建了Agent的节点,已创建的Agent继续使用,不需要重新采集和组织数据;对于新子树中没有创建Agent的节点,则创建相应的采集Agent或组织Agent,并进行相应的数据采集和组织。Collect Agent processing module and organize Agent processing module According to the new subtree, for the nodes in the new subtree that have created Agent, the created Agent will continue to be used without re-collecting and organizing data; for nodes that have not created Agent in the new subtree Node, then create the corresponding collection Agent or organization Agent, and carry out the corresponding data collection and organization. 10.如权利要求7或8所述的系统,其特征在于,各个采集Agent实时监控数据池中的数据,当发现自身所需采集的数据的数量或数值发生变化,则该采集Agent重新进行数据采集工作;10. The system according to claim 7 or 8, wherein each collection agent monitors the data in the data pool in real time, and when it is found that the quantity or value of the data it needs to collect changes, the collection agent re-performs the data collection process. collection work; 各个组织Agent也实时监控作为自身数据来源的Agent,如果发现作为自身数据来源的Agent有数量或数值变化,则该组织Agent重新进行数据组织工作;Each organization Agent also monitors the Agent as its own data source in real time. If it finds that the number or value of the Agent as its own data source has changed, the organization Agent will re-organize the data; 当采集Agent和组织Agent中任意一个Agent的数据发生变化时,均通知三维模型渲染引擎重新将变化后的Agent数据转换为三维模型显示所需的信息,并更新三维地理图像,发送给图形输出设备。When the data of any Agent in the collection Agent and Organization Agent changes, the 3D model rendering engine is notified to re-convert the changed Agent data into the information required for 3D model display, update the 3D geographic image, and send it to the graphics output device .
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