Earthquake emergency collaborative commanding and dispatching system
By constructing an earthquake emergency collaborative command and dispatch system, the problems of data silos and decision-making lag in earthquake emergency command have been solved. It has realized the real-time acquisition and dynamic response of multi-source data, and improved the collaborative efficiency of emergency command and the accuracy of resource allocation.
Patent Information
- Application Number
- CN202511173337.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-21
- Publication Date
- 2025-12-12
AI Technical Summary
The existing earthquake emergency command system suffers from problems such as data fragmentation, poor inter-departmental coordination, and delayed decision-making and response, making it difficult to meet the real-time command needs under complex earthquake situations.
An earthquake emergency collaborative command and dispatch system is constructed, including a data perception module, a collaborative processing module, an intelligent dispatch module, and an interactive display module. Through multi-source data collection, processing, and analysis, an emergency response index and resource dispatch decision-making scheme are generated.
It enables real-time acquisition and integration of multi-source data, dynamically generates emergency response indices, provides a basis for scientific decision-making, generates differentiated dispatching schemes, and improves the coordination efficiency and disaster relief effectiveness of earthquake emergency command.
Smart Images
Figure CN121119752A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of emergency management, and in particular to a seismic emergency collaborative command and dispatch system. BACKGROUND
[0002] Earthquake disasters have the characteristics of strong suddenness, great destructiveness, and many secondary disasters, which pose a serious threat to people's life and property safety and social stability. Seismic emergency command and dispatch, as the core link of earthquake relief work, needs to realize efficient collaboration of multiple links such as seismic monitoring, resource allocation, team command, and information exchange. With the continuous development of seismic monitoring technology in China, various types of monitoring equipment and information systems have been widely used in the emergency field, but the current seismic emergency command still has problems such as data fragmentation, poor department collaboration, and delayed decision response.
[0003] The prior art integrates seismic monitoring data, geographic information data, and social and economic data to build a seismic disaster assessment model, realizing rapid disaster loss assessment and preliminary allocation of rescue forces. However, this system has deficiencies in multi-department resource collaborative dispatch and dynamic response adjustment, making it difficult to meet the real-time command needs under complex seismic conditions.
[0004] In view of this, the present application proposes a seismic emergency collaborative command and dispatch system to solve the problems of insufficient data fusion, low collaboration efficiency, and insufficient decision-making pertinence in the prior art. SUMMARY
[0005] In order to overcome the deficiencies of the prior art, the present application proposes a seismic emergency collaborative command and dispatch system.
[0006] In order to solve the above technical problems, the basic technical solution proposed by the present application is:
[0007] A seismic emergency collaborative command and dispatch system, comprising:
[0008] A data perception module for collecting seismic basic data sets and rescue resource data sets and performing preprocessing, the seismic basic data sets including seismic parameter data, geographic environment data, and secondary disaster data, and the rescue resource data sets including team configuration data, material reserve data, and traffic path data;
[0009] A collaborative processing module for processing the seismic basic data sets and the rescue resource data sets to obtain an emergency response index and perform grading to obtain a rescue priority result;
[0010] An intelligent dispatch module for processing the rescue priority result to obtain a resource dispatch decision scheme;
[0011] An interactive display module is configured to display the dispatching instruction through the command terminal, analyze the earthquake basic data set and the rescue resource data set, and obtain and display the rescue situation result.
[0012] Preferably, the manner of collecting the earthquake basic data set and the rescue resource data set comprises:
[0013] The seismic intensity parameter data, the geographical environment data and the secondary disaster data are obtained by deploying the seismic monitor, the unmanned aerial vehicle aerial equipment and the Internet of Things sensor to collect the seismic intensity source parameter, the topographic feature and the landslide flood risk coefficient respectively;
[0014] The team configuration data is obtained by collecting the number of personnel, the professional type and the real-time position of the rescue team through the emergency management platform;
[0015] The material reserve data is obtained by collecting the reserve quantity and the storage position of the tent, the food and the medicine through the material management system;
[0016] The traffic path data is obtained by collecting the road traffic state and the traffic capacity through the traffic monitoring system; and the preprocessing manner comprises data cleaning, format conversion and outlier removal.
[0017] Preferably, the step of processing the earthquake basic data set and the rescue resource data set comprises:
[0018] The seismic risk value R is obtained by substituting into the calculation formula: seismic risk value R = w1 × A + w2 × B + w3 × C, wherein A is the seismic intensity parameter data, B is the geographical environment data, C is the secondary disaster data, w1, w2 and w3 are corresponding weight factors, the value range of each is 0.1-0.5, and w1 + w2 + w3 = 1;
[0019] The resource guarantee value S is obtained by substituting into the calculation formula: resource guarantee value S = w4 × D + w5 × E + w6 × F, wherein D is the team configuration data, E is the material reserve data, F is the traffic path data, w4, w5 and w6 are corresponding weight factors, the value range of each is 0.2-0.4, and w4 + w5 + w6 = 1; a preset resource threshold interval (Z1, Z2) is set, when the resource guarantee value is greater than Z1 and less than Z2, the value is 1, when the resource guarantee value is less than Z1, the value is 3, and when the resource guarantee value is greater than Z2, the value is 2;
[0020] M groups of historical emergency case vectors are collected as a sample set, the sample set is divided into 70% M of a training set, 15% M of a test set and 15% M of a validation set;
[0021] The priority classification model is established based on the sample set, a historical emergency case vector in the training set is obtained, a first response cluster F1, a second response cluster F2 and a third response cluster F3 are preset, and three data points in the training set are selected as initial cluster centers in a random manner, representing the first response cluster F1, the second response cluster F2 and the third response cluster F3 respectively;
[0022] The distance between data items is obtained by substituting the calculation formula: wherein d(x, y) represents the Euclidean distance between two data points x and y, xi and yi are the values of the data points x and y on the ith sub-data item, and n is the total number of sub-data items; the distances between the data items in the training set and the first response cluster F1, the second response cluster F2 and the third response cluster F3 are calculated, and the data items are assigned to the nearest data cluster to obtain three new data cluster sets as updated cluster centers;
[0023] The means of the three new data cluster sets in the updated cluster centers are calculated respectively as new initial cluster centers for further calculation;
[0024] The rescue priority classification model is obtained when the preset iteration number is reached;
[0025] The fusion vector of the seismic risk value and the resource guarantee value is input into the rescue priority classification model, and an emergency response index is output.
[0026] Preferably, the classification manner comprises:
[0027] A preset emergency response threshold interval (X1, X2) is set, when the emergency response index is less than X1, a third response signal is generated, when the emergency response index is greater than X1 and less than X2, a second response signal is generated, and when the emergency response index is greater than X2, a first response signal is generated;
[0028] The third response signal contains a field representing a low risk of the disaster area, the second response signal contains a field representing a medium risk of the disaster area, and the first response signal contains a field representing a high risk of the disaster area; the third response signal, the second response signal and the first response signal are packaged to obtain a rescue priority result.
[0029] Preferably, the processing manner of the rescue priority result comprises:
[0030] When the rescue priority result is the third response signal, a conventional scheduling scheme is generated, including deploying adjacent area rescue teams for patrol and investigation, and allocating standard quota of basic materials;
[0031] When the rescue priority result is the second response signal, a strengthened scheduling scheme is generated, including sending professional rescue teams to the scene, starting a regional material joint protection mechanism, and opening a temporary traffic channel;
[0032] When the rescue priority result is a first-response signal, an emergency dispatch scheme is generated, including coordinating cross-regional rescue force support, starting a national-level material reserve, implementing traffic control and priority passage measures; the normal dispatch scheme, the enhanced dispatch scheme and the emergency dispatch scheme are packaged to obtain a resource dispatch decision scheme.
[0033] Preferably, the way of analyzing the earthquake basic data set and the rescue resource data set comprises:
[0034] A preset data security threshold interval group is used to compare the earthquake basic data set and the rescue resource data set respectively in the corresponding data security threshold interval to output a safety state, a warning state or a dangerous state.
[0035] When the earthquake basic data set and the rescue resource data set are both safe results, the safety state is output; when one or more than one is a warning result and the rest is a safe result, the warning state is output; when one or more than one is a dangerous result and the rest is a safe result or a warning result, the dangerous state is output; the safety state, the warning state and the dangerous state are packaged to obtain a rescue situation result.
[0036] The beneficial effects of the present application are:
[0037] The present application realizes real-time collection and integration of multi-source earthquake data and rescue resource data through the data perception module, solving the problem of data dispersion and islandization in traditional emergency command; the rescue priority grading model constructed by the collaborative processing module can dynamically generate an emergency response index based on earthquake risk and resource guarantee capacity, providing a scientific basis for decision-making; the intelligent dispatch module generates differentiated dispatch schemes for different response levels, realizing accurate allocation and efficient use of resources; the interactive display module presents the rescue situation in real time, ensuring that the command personnel have a comprehensive understanding of the emergency progress. Overall, the present application has the significant advantages of strong data fusion capability, timely decision-making response and accurate resource dispatch, effectively improving the collaborative efficiency and disaster relief effectiveness of earthquake emergency command. BRIEF DESCRIPTION OF DRAWINGS
[0038] Figure 1 The system block diagram of the earthquake emergency collaborative command and dispatch system of the present application;
[0039] Figure 2 The flowchart of the earthquake emergency collaborative command and dispatch system of the present application. DETAILED DESCRIPTION
[0040] The following will be combined with Figure 1 attached to the attached Figure 2The technical solutions in the embodiments of the present application are clearly and completely described, obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments.
[0041] The present application discloses a kind of earthquake emergency coordination command scheduling systems, comprising:
[0042] Data sensing module, for collecting earthquake basic data set and rescue resource data set, and pre-processing, earthquake basic data set includes earthquake parameter data, geographical environment data and secondary disaster data, rescue resource data set includes team configuration data, material reserve data and traffic path data;The mode of collecting earthquake basic data set and rescue resource data set includes:
[0043] By deploying earthquake monitor, unmanned aerial vehicle aerial equipment and internet of things sensor, respectively collect magnitude source parameter, topographic feature and landslide flood risk coefficient, obtain earthquake parameter data, geographical environment data and secondary disaster data;
[0044] By interfacing emergency management platform, the number of personnel, professional type and real-time position of rescue team are collected, and team configuration data is obtained;
[0045] The reserve quantity and storage location of tent, food and medicine are collected by material management system, and material reserve data is obtained;
[0046] Road traffic state and traffic capacity are collected by traffic monitoring system, and traffic path data is obtained;The mode of pre-processing includes data cleaning, format conversion and outlier rejection.
[0047] Collaborative processing module, for processing earthquake basic data set and rescue resource data set, obtaining emergency response index, and grading, obtaining rescue priority result;The steps of processing earthquake basic data set and rescue resource data set include:
[0048] By substituting calculation formula: earthquake risk value R=w1xA+w2xB+w3xC obtains earthquake risk value, wherein A is earthquake parameter data, B is geographical environment data, C is secondary disaster data, w1, w2 and w3 are corresponding weight factor respectively, the range of value is all 0.1-0.5, and w1+w2+w3=1;
[0049] The resource guarantee value is obtained by substituting into the calculation formula: Resource Guarantee Value S = w4 × D + w5 × E + w6 × F, where D is the team configuration data, E is the material reserve data, and F is the traffic route data. w4, w5, and w6 are the corresponding weight factors, each ranging from 0.2 to 0.4, and w4 + w5 + w6 = 1. The preset resource threshold interval (Z1, Z2) is used. When the resource guarantee value is greater than Z1 and less than Z2, the value is 1; when the resource guarantee value is less than Z1, the value is 3; and when the resource guarantee value is greater than Z2, the value is 2.
[0050] Collect M sets of historical emergency case vectors as a sample set, and divide the sample set into a 70%M training set, a 15%M test set, and a 15%M validation set.
[0051] A priority grading model is established based on the sample set. Historical emergency case vectors are obtained from the training set. First-level response cluster F1, second-level response cluster F2 and third-level response cluster F3 are preset. Three data points are randomly selected in the training set as the initial cluster centers, representing the first-level response cluster F1, the second-level response cluster F2 and the third-level response cluster F3 respectively.
[0052] By substituting into the calculation formula: This gives the distance between data items, where d(x,y) represents the Euclidean distance between two data points x and y. i and y i Let x and y be the values of data points x and y respectively on the i-th sub-data item, and n be the total number of sub-data items; calculate the distances between the data items in the training set and the first-level response cluster F1, the second-level response cluster F2 and the third-level response cluster F3 respectively, and assign the data items to the nearest data cluster to obtain three new data cluster sets as the updated cluster centers;
[0053] The methods for classifying include:
[0054] The emergency response threshold range (X1, X2) is preset. When the emergency response index is less than X1, a level 3 response signal is generated. When the emergency response index is greater than X1 and less than X2, a level 2 response signal is generated. When the emergency response index is greater than X2, a level 1 response signal is generated.
[0055] The Level 3 response signal contains fields representing low risk in the affected area, the Level 2 response signal contains fields representing medium risk in the affected area, and the Level 1 response signal contains fields representing high risk in the affected area. By packaging the Level 3, Level 2, and Level 1 response signals, the rescue priority result is obtained.
[0056] The methods for processing rescue priority results include:
[0057] When the rescue priority result is a tertiary response signal, a regular scheduling scheme is generated, including deploying nearby rescue teams for patrol and investigation, and allocating basic materials according to standard quotas;
[0058] When the rescue priority result is a secondary response signal, a strengthened scheduling scheme is generated, including sending more professional rescue teams to the scene, starting a regional material joint protection mechanism, and opening a temporary traffic channel;
[0059] When the rescue priority result is a primary response signal, an emergency scheduling scheme is generated, including coordinating cross-regional rescue forces, starting a national-level material reserve, and implementing traffic control and priority measures; packaging the regular scheduling scheme, the strengthened scheduling scheme, and the emergency scheduling scheme to obtain a resource scheduling decision scheme.
[0060] The way of analyzing the earthquake basic data set and the rescue resource data set includes:
[0061] A preset data safety threshold interval group is used to compare the earthquake basic data set and the rescue resource data set, and output a safety state, a warning state, or a dangerous state;
[0062] When the earthquake basic data set and the rescue resource data set are both safe results, the safety state is output; when one or more are early warning results, the warning state is output; when one or more are dangerous results, the dangerous state is output; and the safety state, the warning state, and the dangerous state are packaged to obtain a rescue situation result.
[0063] The means of the three new data clusters in the updated cluster center are calculated respectively, and used as new initial cluster centers for further calculation;
[0064] The preset number of iterations is reached, and a rescue priority classification model is obtained;
[0065] The fusion vector of the seismic risk value and the resource guarantee value is input into the rescue priority classification model, and an emergency response index is output.
[0066] An intelligent scheduling module is used to process the rescue priority result and obtain a resource scheduling decision scheme;
[0067] An interactive display module is used to display scheduling instructions through a command terminal, analyze the earthquake basic data set and the rescue resource data set, and obtain and display a rescue situation result.
[0068] The specific implementation is as follows:
[0069] Embodiment 1
[0070] A seismic emergency cooperative command and scheduling system comprises:
[0071] a data sensing module, configured to collect and preprocess a seismic basic dataset and a rescue resource dataset, the seismic basic dataset comprising seismic parameter data, geographical environment data and secondary disaster data, and the rescue resource dataset comprising team configuration data, material reserve data and traffic path data;
[0072] The manner of collecting the seismic basic dataset and the rescue resource dataset comprises:
[0073] The seismic parameter data, the geographical environment data and the secondary disaster data are obtained by deploying a seismic monitor, an unmanned aerial vehicle aerial photography device and an Internet of Things sensor to collect magnitude source parameters, topographic features and landslide flood risk coefficients respectively.
[0074] It is to be explained that the magnitude source parameters are valued as 1-5 according to magnitude, the higher the magnitude, the greater the value, the topographic features are valued as 1-3 according to terrain complexity, and the landslide flood risk coefficients are valued as 1-4 according to occurrence probability.
[0075] The team configuration data is obtained by interfacing an emergency management platform to collect the number of personnel, professional types and real-time positions of rescue teams.
[0076] The material reserve data is obtained by collecting the reserve quantity and storage location of tents, food and medicines through a material management system.
[0077] The traffic path data is obtained by collecting road traffic states and traffic capacities through a traffic monitoring system.
[0078] A collaborative processing module is configured to process the seismic basic dataset and the rescue resource dataset to obtain an emergency response index and grade the index to obtain a rescue priority result.
[0079] The steps of processing the seismic basic dataset and the rescue resource dataset comprise:
[0080] The seismic risk value R is obtained by substituting into the formula: seismic risk value R = w1 x A + w2 x B + w3 x C, wherein A is the seismic parameter data, B is the geographical environment data, C is the secondary disaster data, w1, w2 and w3 are corresponding weight factors, the value range of each is 0.1-0.5, and the sum of the three is 1.
[0081] The resource guarantee value is obtained by substituting into the calculation formula: Resource Guarantee Value S = w4 × d + w5 × E + w6 × F, where D is the team configuration data, E is the material reserve data, F is the transportation route data, and w4, w5, and w6 are the corresponding weight factors, each ranging from 0.2 to 0.4, and the sum of the three is 1. The preset resource threshold interval (Z1, Z2) is: when the resource guarantee value is greater than Z1 and less than Z2, the value is 1; when the resource guarantee value is less than Z1, the value is 3; and when the resource guarantee value is greater than Z2, the value is 2.
[0082] Collect M sets of historical emergency case vectors as a sample set, and divide the sample set into a 70%M training set, a 15%M test set, and a 15%M validation set.
[0083] It should be explained that the historical emergency case vector is a combination of seismic risk values and resource security values from historical seismic events;
[0084] A priority grading model is established based on the sample set. Historical emergency case vectors are obtained from the training set. First-level response cluster F1, second-level response cluster F2 and third-level response cluster F3 are preset. Three data points are randomly selected in the training set as the initial cluster centers, representing the first-level response cluster F1, the second-level response cluster F2 and the third-level response cluster F3 respectively.
[0085] By substituting into the calculation formula: This gives the distance between data items, where d(x,y) represents the Euclidean distance between two data points x and y. i and y i Let x and y be the values of data points x and y respectively on the i-th sub-data item, and n be the total number of sub-data items; calculate the distances between the data items in the training set and the first-level response cluster F1, the second-level response cluster F2 and the third-level response cluster F3 respectively, and assign the data items to the nearest data cluster to obtain three new data cluster sets as the updated cluster centers;
[0086] Calculate the mean of the three new data clusters in the updated cluster center respectively, and use them as the new initial cluster centers for recalculation;
[0087] The rescue priority classification model is obtained by repeating the process until the preset number of iterations is reached (preferably 20).
[0088] The fusion vector of earthquake risk value and resource security value is input into the rescue priority classification model, and the output is the emergency response index.
[0089] The methods for classifying include:
[0090] a preset emergency response threshold interval (X1, X2), when the emergency response index is less than X1, a third-level response signal is generated, when the emergency response index is greater than X1 and less than X2, a second-level response signal is generated, and when the emergency response index is greater than X2, a first-level response signal is generated;
[0091] The third-level response signal comprises a field representing a low risk of the disaster area, the second-level response signal comprises a field representing a medium risk of the disaster area, and the first-level response signal comprises a field representing a high risk of the disaster area;
[0092] The third-level response signal, the second-level response signal and the first-level response signal are packaged to obtain a rescue priority result;
[0093] An intelligent scheduling module is configured to process the rescue priority result to obtain a resource scheduling decision scheme;
[0094] The processing of the rescue priority result comprises:
[0095] When the rescue priority result is the third-level response signal, a regular scheduling scheme is generated, including deploying a rescue team in a neighboring area to conduct a patrol and investigation, and allocating basic materials according to a standard quota;
[0096] When the rescue priority result is the second-level response signal, a strengthened scheduling scheme is generated, including dispatching a professional rescue team to the scene, starting a regional material joint protection mechanism, and opening a temporary traffic channel;
[0097] When the rescue priority result is the first-level response signal, an emergency scheduling scheme is generated, including coordinating cross-regional rescue forces for support, starting a national-level material reserve, and implementing traffic control and priority measures; the regular scheduling scheme, the strengthened scheduling scheme and the emergency scheduling scheme are packaged to obtain the resource scheduling decision scheme;
[0098] An interactive display module is configured to display scheduling instructions through a command terminal, analyze the earthquake basic data set and the rescue resource data set, and obtain and display a rescue situation result;
[0099] The analysis of the earthquake basic data set and the rescue resource data set comprises:
[0100] A preset data security threshold interval group is used to compare the earthquake basic data set and the rescue resource data set in corresponding data security threshold intervals to output a safety state, a warning state or a dangerous state;
[0101] It needs to be explained that the data security threshold interval group is respectively set for the seismic parameter data, the geographical environment data, the secondary disaster data, the team configuration data, the material reserve data and the traffic path data. For example, the seismic parameter threshold interval is (A1, A2). When the seismic parameter data is less than A1, it is a safe result. When it is greater than A1 and less than A2, it is a pre-warning result. When it is greater than A2, it is a dangerous result.
[0102] When the earthquake basic data set and the rescue resource data set are both safe results, a safe state is output. When one or more than one is a pre-warning result and the rest are safe results, a pre-warning state is output. When one or more than one is a dangerous result and the rest are safe results or pre-warning results, a dangerous state is output. The safe state, the pre-warning state and the dangerous state are packaged to obtain a rescue situation result.
[0103] The beneficial effects of the embodiment are that the overall perception of the seismic situation and the resources is realized through multi-source data fusion, the accuracy of the response priority determination is improved through the hierarchical model constructed by the clustering algorithm, the accurate allocation of resources is realized through the differentiated scheduling scheme, the coordination problem in the earthquake emergency command is effectively solved, and the disaster relief efficiency is improved.
[0104] Embodiment 2
[0105] Please refer to Figure 2 The embodiment does not describe some parts in detail, which can be seen from the description of embodiment 1. A seismic emergency coordination command and scheduling method is provided, which includes:
[0106] S1: Collecting an earthquake basic data set and a rescue resource data set and performing preprocessing, the earthquake basic data set including seismic parameter data, geographical environment data and secondary disaster data, and the rescue resource data set including team configuration data, material reserve data and traffic path data;
[0107] S2: Processing the earthquake basic data set and the rescue resource data set to obtain an emergency response index, and performing grading to obtain a rescue priority result;
[0108] S3: Processing the rescue priority result to obtain a resource scheduling decision scheme;
[0109] S4: Displaying the scheduling instruction through a command terminal, analyzing the earthquake basic data set and the rescue resource data set to obtain and display a rescue situation result.
[0110] Those skilled in the art can make various modifications and changes to the above embodiments according to the disclosure and teachings herein. Therefore, the application is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the application shall fall within the protection scope of the claims of the application. In addition, although some specific terms are used in the specification, these terms are only for convenience of description and do not constitute any limitation on the application.
Claims
1. A seismic emergency cooperative command and dispatch system, characterized in that, The method comprises the following steps: A data perception module is used to collect and preprocess a seismic basic data set and a rescue resource data set, wherein the seismic basic data set comprises seismic parameter data, geographical environment data and secondary disaster data, and the rescue resource data set comprises team configuration data, material reserve data and traffic path data; A collaborative processing module is used to process the seismic basic data set and the rescue resource data set, obtain an emergency response index, and perform grading to obtain a rescue priority result; An intelligent scheduling module is used to process the rescue priority result to obtain a resource scheduling decision scheme; An interactive display module is used to display the scheduling instruction through a command terminal, analyze the seismic basic data set and the rescue resource data set, and obtain and display a rescue situation result.
2. The earthquake emergency cooperative command and dispatching system according to claim 1, characterized in that, The method for collecting the seismic basic data set and the rescue resource data set comprises the following steps: Seismic intensity source parameters, topographic features and landslide flood risk coefficients are collected by deploying a seismic monitor, an unmanned aerial vehicle aerial photography device and an Internet of Things sensor to obtain the seismic parameter data, the geographical environment data and the secondary disaster data; The number of personnel, the professional type and the real-time position of a rescue team are collected by interfacing with an emergency management platform to obtain the team configuration data; The reserve quantity and storage position of a tent, food and medicine are collected by a material management system to obtain the material reserve data; The road traffic state and traffic capacity are collected by a traffic monitoring system to obtain the traffic path data; and the preprocessing method comprises data cleaning, format conversion and outlier removal.
3. The earthquake emergency cooperative command and dispatching system according to claim 2, characterized in that, The method for processing the seismic basic data set and the rescue resource data set comprises the following steps: A seismic risk value R is obtained by substituting into a calculation formula: R = w1 × A + w2 × B + w3 × C, wherein A is the seismic parameter data, B is the geographical environment data, C is the secondary disaster data, w1, w2 and w3 are corresponding weight factors, the value range of each of w1, w2 and w3 is 0.1-0.5, and w1 + w2 + w3 = 1; A resource guarantee value S is obtained by substituting into a calculation formula: S = w4 × D + w5 × E + w6 × F, wherein D is the team configuration data, E is the material reserve data, F is the traffic path data, w4, w5 and w6 are corresponding weight factors, the value range of each of w4, w5 and w6 is 0.2-0.4, and w4 + w5 + w6 = 1; a preset resource threshold interval (Z1, Z2) is set, when the resource guarantee value is greater than Z1 and less than Z2, the value is 1, when the resource guarantee value is less than Z1, the value is 3, and when the resource guarantee value is greater than Z2, the value is 2; M groups of historical emergency case vectors are collected as a sample set, the sample set is divided into a 70% M training set, a 15% M test set and a 15% M validation set; A priority grading model is established based on the sample set, historical emergency case vectors in the training set are obtained, a first response cluster F1, a second response cluster F2 and a third response cluster F3 are preset, and three data points in the training set are selected as initial cluster centers in a random manner to represent the first response cluster F1, the second response cluster F2 and the third response cluster F3 respectively; The distance between data items is obtained by substituting the calculation formula: where d(x, y) represents the Euclidean distance between two data points x and y, xi and yi are the values of data points x and y on the i-th sub-data item, and n is the total number of sub-data items; the distances between the data items in the training set and the first-level response cluster F1, the second-level response cluster F2, and the third-level response cluster F3 are calculated, and the data items are assigned to the nearest data cluster to obtain three new data cluster sets as updated cluster centers; The mean values of three new data cluster sets in the updated cluster center are calculated to obtain new initial cluster centers for re-computation. The preset iteration number is reached, and a rescue priority classification model is obtained; The fusion vector of the seismic emotion risk value and the resource guarantee value is input into the rescue priority classification model, and an emergency response index is output.
4. The earthquake emergency cooperative command and dispatching system according to claim 3, characterized in that, The classification manner includes: A preset emergency response threshold interval (X1, X2) is set, when the emergency response index is less than X1, a three-level response signal is generated, when the emergency response index is greater than X1 and less than X2, a two-level response signal is generated, and when the emergency response index is greater than X2, a one-level response signal is generated; The three-level response signal contains a field representing that the risk of the disaster area is low, the two-level response signal contains a field representing that the risk of the disaster area is medium, and the one-level response signal contains a field representing that the risk of the disaster area is high; the three-level response signal, the two-level response signal and the one-level response signal are packaged to obtain a rescue priority result.
5. The earthquake emergency cooperative command and dispatching system according to claim 4, characterized in that, The manner of processing the rescue priority result includes: When the rescue priority result is the three-level response signal, a regular dispatch scheme is generated, including deploying the rescue team in the adjacent area to conduct patrol and investigation, and allocating basic materials according to the standard quota; When the rescue priority result is the two-level response signal, a strengthened dispatch scheme is generated, including increasing the number of professional rescue teams to rush to the scene, starting the regional material joint protection mechanism, and opening a temporary traffic channel; When the rescue priority result is the one-level response signal, an emergency dispatch scheme is generated, including coordinating the cross-regional rescue force to assist, starting the national material reserve, and implementing traffic control and priority measures; the regular dispatch scheme, the strengthened dispatch scheme and the emergency dispatch scheme are packaged to obtain a resource dispatch decision scheme.
6. The earthquake emergency cooperative command and dispatching system according to claim 5, characterized in that, The manner of analyzing the seismic basic data set and the rescue resource data set includes: A preset data security threshold interval group is set, and the seismic basic data set and the rescue resource data set are respectively substituted into the corresponding data security threshold interval for comparison, and a safety state, a warning state or a danger state is output; When the seismic basic data set and the rescue resource data set are both safe results, the safety state is output; when one or more than one is a warning result, the warning state is output; when one or more than one is a danger result, the danger state is output; the safety state, the warning state and the danger state are packaged to obtain a rescue situation result.