Toughness-oriented emergency response scheme optimization method and system
By constructing a multi-level emergency response scheme model and Bayesian network evaluation, the allocation of emergency resources is optimized, which solves the problem of insufficient emergency response schemes in existing technologies and improves system resilience and emergency response effectiveness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIHANG UNIV
- Filing Date
- 2025-12-23
- Publication Date
- 2026-05-19
AI Technical Summary
Existing technologies are insufficient to effectively optimize emergency response plans to improve system resilience, resulting in poor emergency response performance during emergencies.
An emergency response plan model is constructed, including a network topology structure of target layer, perception layer, processing layer, decision layer, and execution layer. The system resilience is evaluated through Bayesian network, and the emergency resource allocation is optimized through genetic algorithm to generate the optimal emergency response plan.
It enables the maximization of emergency response effectiveness, enhances system resilience, and provides efficient and economical emergency response decision support under limited emergency resources.
Smart Images
Figure CN122064939A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of emergency response technology, and more specifically to a method and system for optimizing resilience-oriented emergency response solutions. Background Technology
[0002] Modern society is a typical complex mega-system, composed of infrastructure systems, superstructure systems, productivity systems, and natural environmental systems. With the continuous development of human civilization, modern society has entered the risk society stage, where various complex and uncertain risks are widespread in all areas of society. This has made the security of complex systems such as nations, cities, communities, and infrastructure and transportation networks in modern society a major concern. Sudden events caused by these risks expose modern society to enormous dangers, making emergency management and response effective measures to combat these dangers.
[0003] Emergency response is "the process of responding to extreme events that may cause mass casualties, severe property damage, and disruption of social order by applying scientific, technological, planning, and management methods." After a disaster occurs, emergency response achieves its effect through event perception, response decision-making, and execution, thereby making complex systems such as nations, cities, communities, and infrastructure and transportation networks resilient. Therefore, designing system resilience is essentially designing emergency response plans. The form of emergency system establishment and the optimization of emergency response plans have become decisive factors in whether modern society can achieve optimal resilience, and also a major challenge in current resilience research. At the same time, conducting research on optimizing emergency response plans with the aim of improving resilience provides new methods and ideas for emergency-related work such as safety governance, safe development, and disaster prevention and mitigation. Summary of the Invention
[0004] In view of this, the present invention provides a method and system for optimizing emergency response schemes based on resilience, aiming to solve the above-mentioned technical problems.
[0005] To achieve the above objectives, the present invention adopts the following technical solution: An optimization method for resilience-oriented emergency response schemes includes the following steps: S1. Constructing an emergency response plan model based on the accident evolution network; S2. Conduct system resilience assessment based on the emergency response loop; S3. Based on the system resilience assessment results, optimize the emergency response plan and output the optimized emergency response plan.
[0006] Furthermore, S1 includes: S11. For specific accident types, generate accident evolution Bayesian networks based on historical accident data investigation and statistics. S12. Investigate data on the emergency management system and institutions in the surveyed area to obtain an emergency system model; S13. Based on the accident evolution Bayesian network and the emergency response system model, construct an emergency response scheme model including a target layer, a perception layer, a processing layer, a decision-making layer, and an execution layer.
[0007] Furthermore, S2 includes: S21. Define the entire process of an emergency response system—from sensing an accident, processing information, making decision-making decisions on response plans, and executing controls—as the emergency response loop. S22. Evaluate the closure effectiveness of the emergency response loop in the emergency response plan model to obtain the emergency response effectiveness of the emergency response plan; S23. Based on the combined emergency response effectiveness and the inference results of the accident evolution Bayesian network, assess the system security level; S24. Calculate the system resilience based on the change of the system security level over time.
[0008] Furthermore, in S22, the emergency response efficiency under a single emergency service item... Calculated using the following formula: ,in, This represents the effectiveness of the j-th emergency response loop under the i-th emergency service item.
[0009] Furthermore, in S22, the emergency response effectiveness of emergency response plans under multiple emergency operations... Calculated using the following formula: ,in, This indicates the importance of the i-th emergency response item.
[0010] Furthermore, S3 includes: S31. Generate an initial emergency response plan, the plan including multiple emergency response loops composed of one resource randomly selected from various emergency resources; S32. By increasing the quantity of various emergency resources and performing resource optimization genetic operations, multiple candidate emergency response schemes are generated under different emergency resource quantities. S33. Evaluate the system correction resilience corresponding to each candidate emergency response plan; S34. Output the candidate solution with the best system resilience as the final emergency response solution.
[0011] A resilience-oriented emergency response solution optimization system includes: A user interface module for receiving user input of current location information and accident parameters; an emergency response plan generation module for calling up the location information and accident parameters and generating an emergency response plan through an optimization algorithm; and a system resilience assessment module for assessing the system resilience corresponding to the emergency response plan and communicating with the emergency response plan generation module.
[0012] Furthermore, the emergency response plan generation module defines emergency service types into four categories: fire protection, medical care, public security, and transportation. During initialization, one item is randomly selected from each of the four types of emergency resources to form four emergency response loops to characterize the initial emergency response plan; By continuously increasing the quantity of various emergency resources from few to many, and performing a resource optimization genetic operation based on fitness evaluation for each type of emergency resource quantity, different emergency response plans are generated.
[0013] Furthermore, the system resilience assessment module performs the assessment by calling one or more of the following calculations: performance calculation of a single emergency response loop, performance calculation of emergency response under a single emergency service, performance calculation of emergency response schemes under multiple emergency services, and system resilience calculation based on an integral model.
[0014] Compared with existing technologies, this invention constructs an emergency response plan model oriented towards accident evolution networks. It treats accidents as the object of the emergency response plan, and based on the evolution process of accidents and emergency response procedures in the real world, proposes a network topology structure for emergency response plans comprising five layers: target layer, perception layer, processing layer, decision-making layer, and execution layer. This concretely demonstrates the functions and operations of emergency organizations. Considering that the existence of emergency response plans enables the system to demonstrate resilience against risks, system resilience is regarded as a metric for measuring the effectiveness of the emergency response. By integrating Bayesian inference and emergency response effectiveness assessment, a system safety level assessment is proposed, ultimately completing the system resilience assessment. This resilience assessment method provides a novel approach to selecting the best emergency response plan. This invention aims to achieve the best possible emergency response effect with the least possible emergency resource input as the ultimate goal of emergency response optimization, and can provide a reference for the formulation of emergency response plans for various types and levels of accidents. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0016] Figure 1 This is a diagram illustrating the overall steps of the resilience-oriented emergency response scheme optimization method of the present invention.
[0017] Figure 2 This is a schematic diagram of the resilience-oriented emergency response scheme optimization system of the present invention. Detailed Implementation
[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below. 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.
[0019] See appendix Figure 1-2 To make the above-mentioned objectives of the present invention more apparent and understandable, and to demonstrate the features and advantages of the inventive method, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0020] This embodiment provides a resilience-oriented emergency response plan optimization method and system, which aims to provide efficient and economical emergency response decision support for emergencies by constructing an emergency response plan model, evaluating system resilience, and optimizing the plan. See Figure 2 The emergency response scheme optimization system for resilience described in this embodiment mainly includes the following modules: The user interface module receives user input of the current location (accurate to the district / county level) and accident parameters. The accident parameters include the type and severity of the accident; the location information includes parameters of available emergency organizations in the region, such as the number, size, and location of handling, decision-making, and execution organizations.
[0021] The emergency response plan generation module, communicatively connected to the user interface module, is used to retrieve the regional information and accident parameters, and generate emergency response plans through optimization algorithms. The module operates as follows: First, emergency service types are defined as four categories: fire, medical, public security, and transportation. During initialization, one resource from each of the four categories is randomly selected to form four emergency response loops, representing the initial emergency response plan. Subsequently, the quantity of each type of emergency resource is continuously increased from the least to the most, until the available quantity of a certain type of emergency resource is zero. For each resource quantity, a resource optimization genetic operation based on fitness evaluation (including initial solution construction, selection, crossover, mutation, etc.) is performed to generate different emergency response loop configurations for that resource quantity, i.e., different candidate emergency response plans.
[0022] The system resilience assessment module, communicatively connected to the emergency response plan generation module, is used to evaluate the system resilience corresponding to the candidate emergency response plans provided by the emergency response plan generation module. This module performs the evaluation by calling a series of computational models, mainly including: performance calculation of a single emergency response loop, emergency response performance calculation under a single emergency service, emergency response performance calculation of emergency response plans under multiple emergency services, and system resilience calculation based on an integral model.
[0023] This system is used to provide users with optimized emergency response plans based on the accident situation in a specific region. Its architecture is as follows: Figure 2 As shown: Module 1: User interface, where users input the accident location and accident information, and the system outputs an optimized and resiliently tested emergency response plan.
[0024] Module 2: System Resilience Assessment Module. Conduct system resilience assessments under different emergency response plans according to the steps shown in Step 3.
[0025] Module 3: Emergency Response Plan Generation Module. Execute the emergency response plan generation process shown in step 2.
[0026] The overall flow of the method described in this invention is as follows: Figure 1 As shown, the specific steps include: An emergency response plan model is constructed based on an accident evolution network. For a specific type of accident, historical accident data is investigated and statistically analyzed to determine its evolutionary patterns, generating an accident evolution Bayesian network to describe the causal logic of the accident. Data on the emergency management system and institutions in the current region are investigated, including information on the functions, business types, resource allocation, and affiliations of each emergency organization, to obtain an emergency system model for the region. Based on the obtained accident evolution Bayesian network and the emergency system model derived from the steps, an emergency response plan model is constructed. This model adopts a network topology structure with five layers: target layer, perception layer, processing layer, decision-making layer, and execution layer, concretely demonstrating the functional division and collaborative process of emergency organizations in responding to specific accidents.
[0027] Step 1: Input Emergency Organization Parameters and Accident Parameters. Input the emergency organization parameters and accident parameters for the current accident location (accurate to the district / county level), including the number, scale, and location of the handling, decision-making, and execution organizations, as well as the type and severity of the accident.
[0028] Step 2: Emergency response plan generation and optimization.
[0029] An initial emergency response plan is generated. Emergency service types are defined as four categories: fire, medical, public security, and transportation. The four types of emergency resources that can be mobilized in the accident area are specified as follows: , , , The initial emergency response plan involves randomly selecting one of the four types of emergency resources to form four emergency response loops to characterize the current emergency response plan.
[0030] Emergency response plan optimization. The quantity of various emergency resources is continuously increased from the minimum to the maximum until the available quantity of a certain type of emergency resource is zero. For each emergency resource quantity, initial solution construction and resource optimization genetic operations based on fitness evaluation are continuously performed to obtain different emergency response loop configurations, generating the relatively optimal emergency response plan corresponding to different emergency resource quantity conditions.
[0031] Step 3: System Resilience Assessment. For the systems corresponding to the initial emergency response plan and the optimized emergency response plan, a resilience assessment shall be conducted according to the following procedure: Emergency response effectiveness assessment of a single emergency response loop. Emergency response effectiveness can be defined as the degree to which an emergency organization corresponding to a specific emergency operation, within a specified emergency response time and under specified emergency resource constraints, effectively controls the undesirable consequences of a sudden event through a complete emergency response process of perception, processing, decision-making, and execution. The sequence of emergency organizations involved in the emergency response loop is defined as... The availability vector of the emergency response loop is represented as The credibility matrix is represented as The capability of the i-th emergency organization in the emergency response loop is represented as The emergency response effectiveness of a single emergency response loop can be expressed by the following formula: Emergency response effectiveness evaluation of emergency response plans. A closed emergency response loop represents the process of perception, processing, decision-making, and execution, where one emergency response organization goes to the scene to perform a task. However, the formation of an emergency response plan requires the closure of multiple emergency response loops. Therefore, it is necessary to conduct an emergency response effectiveness evaluation of the entire emergency response plan based on the evaluation of the effectiveness of individual emergency response loops. For situations where multiple emergency organizations jointly complete a single emergency response task, such as multiple fire and rescue teams participating in a fire emergency rescue, the emergency response effectiveness corresponding to the i-th emergency response task is represented as... Let the emergency response effectiveness of the j-th emergency response loop corresponding to the i-th emergency service be expressed as: ,but It can be expressed by the following formula: In situations where multiple emergency organizations collaborate to complete an emergency response mission, such as an explosion causing a fire, with injuries and road damage at the scene, fire and rescue organizations are needed to extinguish the fire, medical organizations to treat the injured, and traffic control organizations to manage traffic at the accident site. The effectiveness of this emergency response is the effectiveness of the emergency response plan, which is expressed as: ,use To indicate the importance of the i-th emergency response item, then It can be expressed by the following formula: System safety level assessment based on Bayesian inference. Risk level is defined as the set of the probability of an accident occurring and the severity of its consequences, expressed as... , , These respectively represent the degree of accident risk and the degree of risk of accident consequences. If we represent the probability of an accident occurring, then the formula for calculating the degree of risk is as follows: System security level and risk level are relative concepts, which can be expressed by the following formula: Considering the impact of emergency response on risk levels, a comprehensive risk assessment of emergency response effectiveness is needed to obtain the system security level under the influence of the emergency response. The effect of emergency response on system security is reflected in both the presence and effectiveness of the emergency response, which can be abstracted as its impact on the Bayesian network of incident evolution. The existence of an emergency response alters both the structure and conditional probability of the Bayesian network. Indicates the emergency response plan for The extent of the impact, in This indicates that the level of risk in considering emergency response is taken into account. It can be expressed by the following formula: Is with The relevant functions, i.e. At this point, the system security level It can be expressed by the following formula: System resilience assessment. A method based on an integral model is used to assess resilience. Indicates the time when the accident began to evolve. Indicates the time when the emergency response was initiated. The system resilience can be calculated using the following formula, which indicates the end time of the emergency response: Step 4: Output the optimal system resilience modification scheme as the final emergency response scheme. The system resilience obtained in Step 3 is modified to obtain the modified system resilience. This represents the system resilience under the k-th type of emergency resource quantity, and the optimal value is output as the emergency response plan. It can be expressed by the following formula: This represents the actual resilience of the system under the condition of the k-th type of emergency resource quantity, i.e., the actual resilience of the system; This represents the number of emergency organizations that actually participate in the emergency response process, given the quantity of the k-th type of emergency resources. This indicates the amount of emergency resources required for an emergency response mission. Let represent the improvement in the actual resilience of the system compared to the inherent resilience of the system when the emergency system is not functioning, given the quantity of the k-th type of emergency resources. The calculation method is shown in Equation (4.3). This is a control coefficient for the proportion of resilience improvement. Although increasing the amount of emergency resources will continuously improve the system's resilience level, it actually becomes increasingly difficult to improve the system's resilience level as the amount of emergency resources continues to increase. This is reflected in the fact that a proportional increase in the amount of emergency resources will result in different proportions of improvement in the system's resilience level. This reflects the different proportions of improvement.
[0032] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.
[0033] The various embodiments described in this specification are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for optimizing resilience-oriented emergency response schemes, characterized in that, Includes the following steps: S1. Constructing an emergency response plan model based on the accident evolution network; S2. Conduct system resilience assessment based on the emergency response loop; S3. Based on the system resilience assessment results, optimize the emergency response plan and output the optimized emergency response plan.
2. The method for optimizing a resilience-oriented emergency response scheme according to claim 1, characterized in that, S1 includes: S11. For specific accident types, generate accident evolution Bayesian networks based on historical accident data investigation and statistics. S12. Investigate data on the emergency management system and institutions in the surveyed area to obtain an emergency system model; S13. Based on the accident evolution Bayesian network and the emergency response system model, construct an emergency response scheme model including a target layer, a perception layer, a processing layer, a decision-making layer, and an execution layer.
3. The method for optimizing a resilience-oriented emergency response scheme according to claim 1, characterized in that, S2 includes: S21. Define the entire process of an emergency response system—from sensing an accident, processing information, making decision-making decisions on response plans, and executing controls—as the emergency response loop. S22. Evaluate the closure effectiveness of the emergency response loop in the emergency response plan model to obtain the emergency response effectiveness of the emergency response plan; S23. Based on the combined emergency response effectiveness and the inference results of the accident evolution Bayesian network, assess the system security level; S24. Calculate the system resilience based on the change of the system security level over time.
4. The method for optimizing a resilience-oriented emergency response scheme according to claim 3, characterized in that, In S22, the emergency response effectiveness under a single emergency service item Calculated using the following formula: ,in, This represents the effectiveness of the j-th emergency response loop under the i-th emergency service item.
5. The method for optimizing a resilience-oriented emergency response scheme according to claim 3, characterized in that, In S22, the emergency response effectiveness of emergency response plans under multiple emergency operations. Calculated using the following formula: ,in, This indicates the importance of the i-th emergency response item.
6. The method for optimizing a resilience-oriented emergency response scheme according to claim 1, characterized in that, S3 includes: S31. Generate an initial emergency response plan, the plan including multiple emergency response loops composed of one resource randomly selected from various emergency resources; S32. By increasing the quantity of various emergency resources and performing resource optimization genetic operations, multiple candidate emergency response schemes are generated under different emergency resource quantities. S33. Evaluate the system correction resilience corresponding to each candidate emergency response plan; S34. Output the candidate solution with the best system resilience as the final emergency response solution.
7. A resilience-oriented emergency response scheme optimization system, based on any one of the resilience-oriented emergency response scheme optimization methods described in claims 1-6, characterized in that, include: A user interface module for receiving user input of current location information and accident parameters; an emergency response plan generation module for calling up the location information and accident parameters and generating an emergency response plan through an optimization algorithm; and a system resilience assessment module for assessing the system resilience corresponding to the emergency response plan and communicating with the emergency response plan generation module.
8. The emergency response scheme optimization system for resilience according to claim 7, characterized in that, The emergency response plan generation module defines emergency service types into four categories: fire protection, medical care, public security, and transportation. During initialization, one item is randomly selected from each of the four types of emergency resources to form four emergency response loops to characterize the initial emergency response plan; By continuously increasing the quantity of various emergency resources from few to many, and performing a resource optimization genetic operation based on fitness evaluation for each type of emergency resource quantity, different emergency response plans are generated.
9. The emergency response scheme optimization system for resilience according to claim 7, characterized in that, The system resilience assessment module performs the assessment by calling one or more of the following calculations: performance calculation of a single emergency response loop, performance calculation of emergency response under a single emergency service, performance calculation of emergency response schemes under multiple emergency services, and system resilience calculation based on an integral model.