A decision utility evaluation system for earthquake emergency information

Abstract

The application discloses a kind of decision utility evaluation systems of earthquake emergency information, comprising: basic data integration module: collection and dynamic update multi-source basic data;Earthquake scenario simulation module: simulate complex earthquake scenario and its influence field including foreshock, main shock and aftershock sequence;Multi-disaster coupling evaluation module: based on simulated earthquake influence, in parallel assesses the risk of earthquake direct damage and various secondary disasters;Disaster chain and network influence analysis module: build disaster event chain logic network to simulate the chain trigger and amplification effect between different disasters, analyze the chain effect of disaster, simultaneously abstract traffic network, rescue force distribution point and emergency supplies warehouse as network model, dynamically evaluate the influence of disaster on network model connectivity, identify key breakpoint and generate resource scheduling and path re-planning scheme;Achievements output module: generate integrated decision support report and map including disaster chain risk, network vulnerability and coping strategy.

Description

Technical Field

[0001] This invention relates to the field of earthquake disaster technology, and in particular to a decision-making effectiveness evaluation system for earthquake emergency information. Background Technology

[0002] With the deepening transformation of earthquake disaster assessment towards operationalization and informatization, traditional methods for predicting earthquake disaster losses are no longer sufficient to meet the needs of dynamic, precise, and collaborative emergency decision-making. Existing research and practice mainly suffer from the following technical limitations: The assessment objects are too singular: most systems still focus on the static risk assessment of a single disaster, or only conduct parallel and independent analysis of multiple disasters, lacking systematic modeling and quantification of the chain triggering and coupling amplification effects between disasters; Insufficient model dynamism: Existing assessment models are mostly based on preset static scenarios and fail to fully integrate real-time monitoring data, making it impossible to achieve dynamic simulation of disaster evolution and rolling updates of risk assessment; Weak chain effect analysis: Although there are conceptual studies that focus on disaster chains, there is a lack of models and methods to quantitatively map chain effects to specific emergency networks and analyze their connectivity impact, resulting in limited support of assessment results for emergency dispatch decisions; Network resilience assessment is lacking: Existing studies rarely incorporate infrastructure networks and emergency resource networks into a unified analysis framework, failing to identify and dynamically replan key network nodes / edges under disaster impacts.

[0003] Therefore, there is an urgent need for a decision-making effectiveness evaluation system for earthquake emergency information. This system should be able to integrate dynamic earthquake sequence simulation, multi-hazard coupling assessment, and disaster chain network analysis to achieve a leap from disaster prediction to decision support and improve the scientific nature and timeliness of emergency response. Summary of the Invention

[0004] The purpose of this invention is to overcome the technical defects of existing technologies, such as the singularity of evaluation objects, insufficient model dynamism, weak chain effect analysis, and lack of network resilience assessment. It provides an earthquake emergency information decision-making utility assessment system that integrates dynamic earthquake sequence simulation, multi-hazard coupling assessment, disaster chain network analysis, and emergency network resilience assessment, so as to achieve a leap from disaster prediction to decision support.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: An earthquake emergency information decision-making effectiveness evaluation system, characterized in that it includes a basic data integration module, an earthquake scenario simulation module, a multi-hazard coupling evaluation module, a hazard chain and network impact analysis module, and a results output module connected in sequence. The basic data integration module is used to collect and dynamically update multi-source basic data, including administrative divisions, population and economy, building characteristics, geological environment, major facilities and historical disasters; The earthquake scenario simulation module, based on data and preset parameters obtained from the basic data integration module, simulates complex earthquake scenarios and their impact fields, including foreshocks, mainshocks, and aftershock sequences. This module integrates a dynamic earthquake event sequence simulation engine, which connects to real-time earthquake monitoring data streams and dynamically adjusts the magnitude and probability of subsequent earthquake events based on time-dependent probabilistic earthquake hazard analysis models (such as the ETAS model, see Ogata, 1988; Werner et al., 2011), simulating the spatiotemporal superposition effects of multiple earthquake events. The multi-hazard coupling assessment module, based on a simulated earthquake impact field, assesses the risk of direct earthquake damage and various secondary disasters in parallel. This module integrates a multi-source secondary disaster assessment model library, including risk assessment models for landslides, fires, hazardous chemical leaks, lifeline engineering damage, and dam failures. The disaster chain and network impact analysis module is used to construct a logical network of disaster event chains to simulate the chain triggering and amplification effects between different disasters, and to abstract the transportation network, the distribution points of rescue forces and the emergency material reserve into a network model, dynamically assess the impact of disasters on network connectivity, identify key interruption points and generate resource scheduling and path replanning schemes. The output module is used to integrate the analysis results of the aforementioned modules and generate a comprehensive decision support report and maps that include a disaster chain risk map, network vulnerability analysis, and response strategies.

[0006] The above plan further includes: Furthermore, the basic data integration module includes a building asset dynamic management unit, which is linked with the city information model platform through a secure interface to update the building's structural attributes, fortification standards, and vulnerability data in real time.

[0007] Furthermore, the workflow of the disaster chain and network impact analysis module includes: Construct a disaster event chain logic network based on predefined disaster triggering rules, and analyze the chain development relationship; The emergency resource points and transportation network are abstracted into a network model, and the failure status of nodes and edges is dynamically calculated. We use graph theory to dynamically calculate key indicators of network connectivity, identify critical interruption points, and generate scheduling and path replanning schemes.

[0008] Furthermore, the method for identifying key breakpoints includes: Construct a physical network graph theory model and initialize its state; Based on the updated network state, the shortest path algorithm in graph theory is used to analyze the connectivity, evaluate the overall network efficiency, and calculate the centrality index of nodes and edges. By comparing pre-disaster and post-disaster indicators, key disruption points that meet one of the following conditions can be identified: The individual's condition changes from normal to interrupted or severely reduced; This causes the shortest path between one or more "rescue-disaster" node pairs to fail or the travel time to surge beyond a threshold. Centrality indicators in post-disaster networks have increased significantly; Sort and output the impact levels of critical interruption points.

[0009] Furthermore, the system also includes a business management and training collaboration module, which coordinates task processes, manages data quality and versions, and supports multi-department data sharing and closed-loop feedback.

[0010] The present invention has the following beneficial effects: In this invention, by constructing a disaster event chain logic network, the traditional parallel multi-hazard assessment is upgraded to a quantitative analysis of chain-triggered and amplified effects, which solves the weakness of existing disaster correlation analysis technology. A dynamic earthquake sequence simulation engine based on real-time monitoring data is introduced, which enables subsequent multi-hazard assessment and network analysis to be updated in a rolling manner with earthquake evolution, breaking through the timeliness bottleneck of static scenarios. The disaster chain output is directly mapped to the emergency resource network graph theory model, realizing the quantitative transformation from where the disaster occurred to how emergency response capabilities were damaged. By identifying key interruption points and generating dynamic replanning schemes, precise countermeasures for emergency command to break the chain, protect the network, and optimize scheduling are provided, achieving a qualitative leap in decision-making effectiveness. Attached Figure Description

[0011] Figure 1 This is a system block diagram of an earthquake emergency information decision-making effectiveness evaluation system proposed in this invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] Please see Figure 1 As shown, the present invention is a decision utility evaluation system for earthquake emergency information, comprising a basic data integration module, an earthquake scenario simulation module, a multi-hazard coupling evaluation module, a hazard chain and network impact analysis module, and a results output module connected in sequence. The basic data integration module collects and dynamically updates multi-source basic data, including administrative divisions, population and economy, building characteristics, geological environment, major facilities and historical disasters. The basic data includes administrative division information, population distribution data, building structural characteristic data, economic statistics, geospatial vector data, historical earthquake data, geological disaster hazard point data, transportation network data, distribution data of major engineering facilities and secondary disaster hazard source data. The earthquake scenario simulation module simulates complex earthquake scenarios and their influence fields, including foreshocks, mainshocks, and aftershocks, based on data obtained from the basic data integration module and preset parameters. The preset parameters include magnitude and spatial distribution parameters. The multi-hazard coupling assessment module: based on simulated earthquake impacts, it assesses the risks of direct earthquake damage and various secondary hazards in parallel. The types of secondary hazards include at least landslides, collapses, fires, hazardous chemical leaks, damage to lifeline engineering projects, and dam failures. The disaster chain and network impact analysis module constructs a logical network of disaster event chains to simulate the chain triggering and amplification effects between different disasters, analyzes the disaster chain effect, and abstracts the transportation network, the distribution points of rescue forces, and the emergency material reserve into a network model. It dynamically evaluates the impact of disasters on the connectivity of the network model, identifies key interruption points, and generates resource scheduling and path replanning schemes. The output module integrates the analysis results from the aforementioned modules to generate a comprehensive decision support report and maps that include disaster chain risks, network vulnerabilities, and response strategies.

[0014] like Figure 1 As shown, the system of this invention consists of a basic data integration module, an earthquake scenario simulation module, a multi-hazard coupling assessment module, a hazard chain and network impact analysis module, a results output module, and an optional business management and training collaboration module. Each module is sequentially connected via communication, forming a closed-loop process from data acquisition, scenario simulation, risk assessment, network analysis to decision support. The basic data integration module acquires and integrates data on administrative divisions, population and economy, building assets, geological environment, and historical disasters through multi-source interfaces. Among them, the building asset dynamic management unit connects with the urban information model platform to realize real-time updates of building information and ensure the timeliness of assessment data. The earthquake scenario simulation module integrates a time-dependent probabilistic earthquake hazard analysis engine based on the ETAS model, accesses real-time earthquake monitoring data streams, dynamically generates sequence scenarios including foreshocks, mainshocks, and aftershocks, simulates their spatiotemporal superposition effects, and provides dynamic input for subsequent assessments. The multi-hazard coupling assessment module calls upon embedded professional assessment models for landslides, fires, leaks, lifeline engineering damage, and dam failures, combining ground motion intensity with the distribution of disaster-bearing bodies to perform parallel or selective risk assessments and output a multi-hazard coupling risk map. Existing research largely remains at the conceptual framework of hazard chains (Gill & Malamud, 2014). This invention achieves a breakthrough from concept to computation by coupling a parallel assessment model library with a hazard chain logical network. The disaster chain and network impact analysis module is one of the core innovations of this invention. This module first constructs a disaster chain logical network based on a disaster triggering rule base to quantify the chain effect; then, it abstracts the emergency resource network into a graph theory model to dynamically calculate the changes in node and edge states caused by the disaster; finally, it identifies key interruption points and generates resource scheduling and path replanning suggestions through graph theory methods such as shortest path analysis, network efficiency assessment, and centrality index calculation. Existing network resilience research is mostly based on static assumptions (Dueñas-Osorio & Kwasinski, 2012). This invention achieves dynamic resilience assessment of disaster-network coupling by dynamically accessing the disaster chain output. The output module integrates the above results into a disaster chain risk map, an emergency network vulnerability thematic map, and a resource allocation plan, and outputs them in the form of a visual report to provide intuitive support for command and decision-making. The Business Management and Training Collaboration module is responsible for system operation and maintenance, data version management, cross-departmental collaboration and personnel training, ensuring the continuous and stable operation of the system and the business application of evaluation results; Through the coordinated operation of the above modules, this invention achieves quantitative simulation of earthquake disaster chain effects, dynamic assessment of emergency network connectivity, and real-time generation of decision support information, significantly improving the scientific nature, accuracy, and timeliness of earthquake emergency response.

[0015] In one embodiment, the earthquake scenario simulation module integrates a dynamic earthquake event sequence simulation engine. The simulation engine accesses real-time earthquake monitoring data streams and dynamically adjusts the magnitude and probability of subsequent earthquake events based on a time-dependent probabilistic earthquake hazard analysis model, simulating the spatiotemporal superposition effects of multiple earthquake events.

[0016] It should be noted that the specific analysis process performed by the dynamic seismic event sequence simulation engine is as follows: The system can access and process earthquake monitoring data streams in real time, acquire real-time observation data including microseismic sequences and foreshock activity, and initialize the basic geological parameters and user-defined initial source parameters required for earthquake sequence simulation. The initial source parameters include, but are not limited to, initial magnitude, seismogenic structure geometry, fault segmentation stick-slip characteristic parameters, and regional background stress field direction. These parameters together constitute the initial boundary conditions of the time-dependent probabilistic seismic hazard analysis model. Based on a time-dependent probabilistic seismic hazard analysis model, combined with processed real-time data, fault friction parameters, and stress triggering models, a sequence of potential seismic events, including foreshocks, mainshocks, and aftershocks, is dynamically generated and updated. The magnitude and probability of occurrence of each subsequent event are dynamically adjusted based on the triggering effect of previous events and the regional stress state. The process of dynamically generating and updating the seismic event sequence is iterative. After each new real-time monitoring data is input or a new seismic event is simulated, the engine immediately recalculates the changes in the regional stress field and updates the rupture probability, possible magnitude, and spatial distribution of subsequent potential events accordingly. The spatiotemporal evolution of the generated dynamic seismic event sequence is simulated to calculate the superimposed impact field of multiple seismic events in time and space, and to comprehensively assess the resulting cumulative building damage, the stepwise increase in casualties, and the initial risk of the triggered secondary disaster chain. The calculation of the superimposed influence field of multiple earthquake events specifically includes: The seismic intensity attenuation model was used to calculate the impact field of each seismic event in the sequence, and the intensity value, ground motion parameters and the resulting direct building damage were linearly or nonlinearly superimposed and accumulated on the spatiotemporal grid to quantify the cumulative enhancement process of the disaster effect. The building vulnerability matrix used in the comprehensive assessment of cumulative building damage is dynamically updated. This matrix can obtain the latest building reinforcement or demolition information from the city information model through the system interface, thereby reflecting the real-time status of the building's seismic resistance. Based on the simulation results, the system dynamically outputs the evolution trend of the earthquake sequence, the comprehensive impact assessment results at each stage, and key risk spatiotemporal distribution information, providing dynamically updated scenario inputs for disaster chain analysis and emergency decision-making.

[0017] In one embodiment, the basic data integration module includes a building asset dynamic management unit. This building asset dynamic management unit links with the urban building information model or urban information model platform through a secure interface to obtain information on building construction, renovation, and demolition, and updates the building's structural attributes, fortification standards, and corresponding vulnerability data in real time.

[0018] In one embodiment, the multi-hazard coupling assessment module integrates a multi-source secondary hazard assessment model library including landslides, fires, hazardous chemical leaks, lifeline engineering damage, and reservoir dam failure risks, and performs parallel or selective risk assessments by combining ground motion intensity and disaster-bearing body distribution data.

[0019] It should be noted that the specific analysis process for risk assessment by the multi-hazard coupling assessment module is as follows: The system receives ground motion intensity distribution data output from the earthquake scenario simulation module and disaster-bearing body distribution data from the basic data integration module. The disaster-bearing body distribution data includes spatial information of buildings, lifeline engineering, hazard sources, and natural environmental elements. Based on predefined disaster types and triggering conditions, corresponding professional assessment models are called in parallel or selectively from the multi-source secondary disaster assessment model library. The triggering conditions include at least: automatically calling the landslide assessment model when the local ground motion intensity exceeds a preset threshold and there is a steep slope; automatically calling the fire or leakage assessment model when there are gas pipelines or chemical facilities in the assessment area and the degree of building damage reaches a certain level; and automatically calling the dam stability assessment model when the assessment area includes a reservoir dam. The earthquake intensity distribution data and the corresponding disaster-bearing body distribution data are input into each of the called assessment models, and calculations are performed simultaneously to obtain preliminary assessment results for landslide hazard level, fire occurrence probability and spread range, hazardous chemical leakage and diffusion risk zone, lifeline engineering function loss status, and reservoir dam stability and dam failure impact range. The preliminary assessment results output by various professional models are superimposed and fused according to a unified spatial reference system and risk assessment grading standard to generate a multi-hazard coupled risk map that comprehensively reflects the spatial distribution and hazard level of various secondary disasters. The fusion process includes standardizing and quantifying the assessment results of different models, and calculating the comprehensive risk index within the grid cell based on preset weights or disaster chain logical relationships. Finally, a visualized multi-hazard coupled risk map is generated through rendering. The multi-hazard coupling risk map and detailed assessment results are output to the disaster chain and network impact analysis module as the basic input data for analyzing disaster chain effects and network impacts.

[0020] In one embodiment, the specific workflow of the disaster chain and network impact analysis module is as follows: First, analyze the chain-like development relationship between disasters based on predefined disaster triggering rules; It should be noted that the specific analytical process for analyzing the chain-like development relationships between disasters is as follows: First, this module systematically constructs a logical network of disaster event chains based on a predefined disaster triggering rule base. This network uses direct earthquake disasters (such as building damage and ground shaking) as initial nodes and various secondary disasters (such as landslides, fires, and leaks) as subsequent nodes, with directed edges explicitly representing the causal relationships and trigger probabilities between disaster events. By traversing this logical network, the module dynamically analyzes how the initial disaster triggers subsequent disasters in a chain-like manner according to preset rules under specific earthquake influence field conditions, and calculates the comprehensive risk evolution path under the chain-like development relationship. Subsequently, emergency resource points and transportation networks are abstracted into a network model, and the failure states of network nodes and edges caused by disasters are dynamically calculated. It should be noted that the specific analysis process for calculating the failure state of network nodes and edges caused by disasters is as follows: The module abstracts key elements such as real-world transportation networks, emergency shelters, medical rescue institutions, material reserves, and command centers into a topological model containing network nodes and edges. Nodes represent critical facilities or resource points, and edges represent connecting paths. Based on the spatial impact range and intensity derived from the aforementioned disaster chain analysis, this step dynamically calculates and updates the failure status and attributes (such as the percentage reduction in traffic capacity) of corresponding nodes (e.g., damaged hospitals) and edges (e.g., roads buried by landslides) in the model, reflecting the damage to the physical emergency network in real time. Finally, key interruption points are identified and resource scheduling and path replanning schemes are generated.

[0021] In one embodiment, the specific steps for identifying key interruption points and generating resource scheduling and path replanning schemes are as follows: Physical network graph theory model construction and state initialization: Each key element in the emergency physical network model (such as road intersections, bridge ends, rescue stations, and supply depots) is abstracted as a node in graph theory, and the connections between key elements (such as road segments and rescue accessibility relationships) are abstracted as edges. Initial attributes are assigned to each node and edge, including type, capacity, traffic capacity, or service capacity values. The failure states of network nodes and edges caused by disasters are calculated, and the states of nodes and edges affected by disasters are marked. Dynamic calculation of key network connectivity indicators: Based on the updated network state, the shortest path algorithm in graph theory is used to analyze the traversal capacity, evaluate the overall network efficiency, and calculate the centrality indicators of nodes and edges. Shortest reachability path analysis: For each pair of "rescue force node - disaster area node", the following algorithms are used, but not limited to Dijkstra's algorithm and A... The algorithm, or Floyd algorithm, is used to calculate the shortest travel time or distance between rescue force nodes and disaster area nodes. The centrality index includes, but is not limited to, betweenness centrality, closeness centrality, or degree centrality, which is used to identify nodes or edges that play a key role in the network. The travel delay index is obtained by comparing it with the pre-disaster baseline value.

[0022] Overall network efficiency assessment: The reciprocal of the harmonic mean of the shortest path lengths between all pairs of nodes in the current network is used as the overall network efficiency to quantify the global accessibility level of the network. A decrease in efficiency value indicates a deterioration in connectivity.

[0023] Betweenness centrality analysis of nodes and edges: This involves calculating the betweenness centrality of each node and edge in the current state, which is the proportion of all shortest paths that pass through that node or edge. This metric identifies the elements that play the most critical pivotal role in the flow of information and resources in the network; their failure will cause the greatest damage to global connectivity. Comparison of general changes and location of critical breakpoints: A systematic comparative analysis is performed between the post-disaster dynamically calculated key indicators (such as shortest path set, overall efficiency value, and betweenness centrality ranking) and the pre-disaster baseline state to identify nodes or edges that meet the judgment criteria, which are then identified as critical breakpoints. These judgment criteria include: The individual's condition changes from normal to interrupted or severely reduced; Failure results in the shortest reachable path between one or more rescue force nodes and disaster area nodes no longer existing, or the travel time surges beyond a preset threshold; The betweenness centrality ranking in post-disaster networks has jumped significantly, indicating that it has become an indispensable bottleneck in current vulnerable networks, and its risk of further failure is extremely high. Disruption Point Impact Ranking and Output: For all identified critical disruption points, their impact levels are ranked based on the degree of travel delay caused, the number of affected rescue node pairs, and their betweenness centrality value in the current network. The ranked list of critical disruption points and their specific impact analysis (such as the affected critical rescue routes) are then output in a structured format.

[0024] In one embodiment, the output module receives the results of disaster chain analysis and network impact assessment, generates a comprehensive disaster chain risk map and a dynamic emergency resource allocation suggestion map, intuitively displays the chain disaster effects and their impact on emergency response capabilities, and provides spatial visualization support for command and decision-making.

[0025] In one embodiment, a business management and training collaboration module is included. This module coordinates the task processes of each module, manages data quality and versions, and organizes professional training for complex scenario simulation, multi-hazard assessment, and disaster chain analysis to improve the operational level of the system. The system connects with the business platforms of local government emergency management, natural resources, housing and construction departments through standardized data interfaces to achieve dynamic sharing and closed-loop feedback of basic data and assessment results, ensuring the effectiveness and timeliness of the assessment.

[0026] A method for evaluating the decision-making utility of earthquake emergency information, using the earthquake emergency information decision-making utility evaluation system as described in claim 1, is characterized by comprising the following steps: Collect and dynamically update multi-source basic data; Based on real-time earthquake monitoring data and probabilistic earthquake hazard models, earthquake sequence scenarios and their impact fields are dynamically simulated. Parallel assessment of direct earthquake damage and the risk of multiple secondary disasters; Construct a disaster chain logical network and an emergency resource graph theory model, analyze the impact of chain effects and network connectivity, and identify key breakpoints; Generate and output disaster chain risk maps, network vulnerability analysis, and resource scheduling schemes.

[0027] All data obtained in this invention has been authorized by the user.

[0028] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A decision-making effectiveness evaluation system for earthquake emergency information, characterized in that, It includes a basic data integration module for communication connections, an earthquake scenario simulation module, a multi-hazard coupling assessment module, a hazard chain and network impact analysis module, and a results output module; The basic data integration module collects and dynamically updates multi-source basic data; The earthquake scenario simulation module simulates earthquake scenarios and their impact fields, including foreshocks, mainshocks, and aftershocks, based on the basic data and preset parameters. It also integrates a dynamic earthquake event sequence simulation engine, which connects to real-time earthquake monitoring data streams and dynamically adjusts subsequent earthquake event parameters based on a time-dependent probabilistic earthquake hazard analysis model. The multi-hazard coupling assessment module: based on the earthquake impact field, assesses the risks of direct earthquake damage and various secondary disasters in parallel; The disaster chain and network impact analysis module: constructs a logical network of disaster event chains to simulate chain effects, abstracts the emergency resource network into a graph theory model, dynamically evaluates the impact of disasters on network connectivity, identifies key interruption points, and generates resource scheduling and path replanning schemes; The output module generates decision support reports and maps that include disaster chain risks, network vulnerabilities, and response strategies.

2. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, The dynamic earthquake event sequence simulation engine is based on the ETAS model and is used to simulate the spatiotemporal superposition effects of multiple earthquake events.

3. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, The basic data integration module includes a building asset dynamic management unit, which is used to link with the city information model platform through a secure interface to update building attributes and vulnerability data in real time.

4. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, The multi-hazard coupling assessment module integrates a risk assessment model library for landslides, fires, hazardous chemical leaks, lifeline engineering damage, and dam failures, supporting parallel or selective risk assessment.

5. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, The workflow of the disaster chain and network impact analysis module includes: Construct a logical network of disaster event chains based on disaster triggering rules; The emergency resource network is abstracted into a graph theory model, and the state of nodes and edges is dynamically calculated. Graph theory is used to identify critical breakpoints and generate scheduling and path replanning schemes.

6. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, The identification of key interruption points includes: Construct and initialize the network graph theory model; Based on the updated network state, the shortest path algorithm in graph theory is used to analyze the connectivity, evaluate the overall network efficiency, and calculate the centrality index of nodes and edges. By comparing pre-disaster and post-disaster conditions, key interruption points that meet the preset criteria are identified. Sort and output the impact levels of critical interruption points.

7. The earthquake emergency information decision-making effectiveness evaluation system according to claim 1, characterized in that, It includes a business management and training collaboration module, which is used to coordinate the task processes of each module, manage data quality and version, and organize professional training for complex scenario simulation, multi-hazard assessment and disaster chain analysis.

8. A method for evaluating the decision-making utility of earthquake emergency information, using the earthquake emergency information decision-making utility evaluation system as described in claim 1, characterized in that, Includes the following steps: Collect and dynamically update multi-source basic data; Based on real-time earthquake monitoring data and probabilistic earthquake hazard models, earthquake sequence scenarios and their impact fields are dynamically simulated. Parallel assessment of direct earthquake damage and the risk of multiple secondary disasters; Construct a disaster chain logical network and an emergency resource graph theory model, analyze the impact of chain effects and network connectivity, and identify key breakpoints; Generate and output disaster chain risk maps, network vulnerability analysis, and resource scheduling schemes.

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