Airport emergency response network toughness analysis method and system under emergencies and storage medium

Abstract

The invention provides an airport emergency response network toughness analysis method and system under emergencies, and a storage medium. The method comprises the following steps: identifying and determining key element nodes of emergency response under airport emergencies based on a plan file; establishing links among the nodes of the airport emergency response network under the emergencies according to the relationship among the key element nodes, and representing the links by using a binary matrix; constructing an airport emergency response network under an emergency; and carrying out three-stage toughness measurement analysis on the constructed network. According to the method, multi-dimensional contents such as a main body, resources and tasks are fused, an emergency response network model is constructed for an airport emergency response operation mechanism by applying a meta-network method, an emergency plan of an emergency response network is modeled and evaluated from the perspective of overall layout, and the network toughness is measured and analyzed, so that the emergency response network is obtained. Defects in plans are cleared and further improvement is made, the toughness level of an airport for coping with emergencies can be improved, and defects in existing airport complex network toughness analysis are made up.

Description

Technical Field

[0001] The present invention belongs to the technical field of emergency response network resilience analysis, and in particular relates to an airport emergency response network resilience analysis method under emergencies. Background Art

[0002] Airport emergencies involve the interaction between multiple entities, with complex associations and difficult to control dynamic changes. The traditional emergency management model will face difficulties in system organization adaptation, personnel vacancies and dislocations, and long recovery time. It will cause serious impacts such as flight cancellations, flight delays, and long rescue time and huge losses, affecting the normal operation of the entire airport. Therefore, it is necessary to study the resilience of airport emergency response networks under emergencies in order to enhance the resilience of airport infrastructure operations and emergency activities in the future. However, the current research on the resilience of airport complex networks mainly focuses on the resilience of airport flight areas and air traffic networks, and the impact of airport emergency response network resilience under emergencies needs to be studied. Therefore, it is necessary to deeply analyze the resilience indicators of airport emergency response networks under emergencies and establish corresponding response strategies and mechanisms to enhance the overall response capabilities of airports in the face of emergencies and ensure the safety and stable operation of the aviation transportation system. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides a method, system and storage medium for analyzing the resilience of an airport emergency response network under emergencies, which makes up for the deficiencies in the existing airport complex network resilience analysis.

[0004] The present invention achieves the above technical objectives through the following technical means.

[0005] A method for analyzing the resilience of an airport emergency response network under an emergency event includes the following steps:

[0006] Step 1: Identify the key elements of emergency response before, during and after an airport emergency occurs;

[0007] Step 2: Based on the relationship between the key element nodes, create the links between the nodes of the airport emergency response network under emergencies, and use a binary matrix to represent it;

[0008] Step 3: Based on the binary matrix, construct the airport emergency response network under emergencies;

[0009] Step 4: Conduct a three-stage network resilience measurement analysis.

[0010] Furthermore, the key element nodes include: subject (A), resource (R), knowledge (K), task (T); the binary matrix includes: [AA], [AT], [AR], [AK], [RT], [KT].

[0011] Furthermore, in the step 4, in the first stage of resilience measurement analysis, three indicators, namely natural connectivity, overall task completion, and task resource / knowledge consistency, are used for measurement;

[0012] In the second stage of resilience measurement analysis, three indicators, efficiency, performance accuracy, and overall task completion, were used for measurement;

[0013] In the third stage of resilience measurement analysis, three indicators are used for measurement: average speed, personnel cost, and cognitive demand.

[0014] Furthermore, the natural connectivity evaluates the structural robustness of the network in the face of failures by measuring the redundancy of alternative paths:

[0015]

[0016] Robustness refers to the ability of elements and systems to withstand a certain degree of interference without suffering functional loss; AA represents the AA emergency response network; AA represents the binary matrix of the AA emergency response network; λ j (j=1,...,m) represents the eigenvalue of the matrix [AA]; m represents the total number of eigenvalues; R Rob Indicates the robustness of each stage of the network; represents the eigenvalue power with e as the base; the maximum robustness means that when organizations are fully connected and cooperate with each other, G AA The maximum natural connectivity is achieved; while the minimum robustness means that when all stakeholders do not cooperate, G AA Achieve minimum natural connectivity.

[0017] Further, the overall task completion represents the percentage of tasks that can be completed by a subject with the required resources and knowledge;

[0018]

[0019] Among them, R OTC Indicates the overall task completion, |T| refers to the total number of tasks that need to be completed; |S RK |The number of tasks that could not be completed based on whether the subject had the necessary resources and knowledge to perform the task;

[0020]

[0021] Where i represents the row in the binary matrix; j represents the column in the binary matrix; N RK is the knowledge / resource gap matrix, which refers to the gap between the knowledge / resources required to complete the task and the knowledge / resources available to the subject; N RK (i,j) is the matrix NRK The element in the i-th row and j-th column; AT is the binary matrix corresponding to the AT network; AT T is the transpose of the matrix [AT]; AR is the binary matrix corresponding to the AR network; AK is the binary matrix corresponding to the AK network; RT is the binary matrix corresponding to the KT network; KT is the binary matrix corresponding to the KT network; [RT KT] T is the transposed matrix of [RT KT].

[0022] Furthermore, the task resource / knowledge consistency refers to the amount of resources and knowledge that the subject does not need to complete the task:

[0023]

[0024] Among them, R TRW Indicates the amount of resources that the subject does not need to complete the task, R TKW represents the amount of knowledge that the subject does not need when completing the task, m represents the total number of rows in the binary matrix, K1 represents the demand relationship between tasks and resources within the network, n represents the total number of columns in the binary matrix, K2 represents the demand relationship between tasks and knowledge within the network, and ~RT T Indicates whether the resource is needed to complete the task within the network; ~KT T Indicates whether the knowledge is needed to complete the task within the network; X(i,j) is the element in the i-th row and j-th column of the matrix X.

[0025] Further, efficiency refers to the degree to which each component in the network contains the minimum links required to maintain connectivity:

[0026]

[0027] Penalty=m-n+K

[0028]

[0029] Among them, R EF represents efficiency, which refers to the degree to which each component in the network contains the minimum links required to maintain connectivity. Penalty represents the number of unconnected chains in the network. A is a unimodal input network with m edges and n nodes. Let K be the number of elements in A, and k i is the size of component i.

[0030] Furthermore, the performance accuracy refers to the degree to which the subject can accurately perform the assigned tasks based on the acquired knowledge and resources:

[0031] Let b be the cardinality of the knowledge node set K, N be the transpose of the matrix [KT], and S be the matrix [AK];

[0032] The correct classification of b with respect to task t is defined as:

[0033]

[0034] The classification of b by subject i with respect to task t is defined as:

[0035]

[0036]

[0037] The group of agents assigned to task t classifies b using majority voting:

[0038]

[0039] When gans=tans, the tasks are classified and the classification is repeated multiple times for each task;

[0040] Among them, true answer represents the correct classification of subject A regarding b relative to task T; N tk Indicates the availability of tasks and knowledge within the network; b k Indicates the length of a two-dimensional string of length K; R it Indicates that subject i believes that this knowledge is necessary to complete the task; S ij A binary matrix representing subject and knowledge; answer i Indicates the number of correct classifications of b by subject A on task T; gans i represents the group of subjects assigned to task t to classify b using majority voting; |I| represents the number of subjects' classifications of b with respect to task t; k represents the length of the two-dimensional string; i represents the row in the binary matrix.

[0041] Furthermore, the average speed refers to the average speed at which any two nodes can interact:

[0042]

[0043] Among them, R AS represents the average speed at which any two nodes can interact; n represents the number of columns of the binary matrix; i represents the row of the binary matrix; G AA It is the AA emergency response network; i is the minimum path sum:

[0044]

[0045] Where D is G AA distance matrix; if there is a path between node i and node u, then D(i,u) is the shortest path between node i and node u.

[0046] A system for implementing the above-mentioned airport emergency response network resilience analysis method under emergency events, comprising:

[0047] The data acquisition and identification module is used to obtain data from the airport's emergency plan files and identify and obtain the four key elements of the subject, resource, knowledge, and task of emergency response in the three stages before, during, and after an airport emergency occurs;

[0048] The link creation module creates links between nodes based on the key element nodes identified by the data acquisition and identification module, and represents them using a binary matrix;

[0049] The emergency response network construction module builds a three-stage airport emergency response network for emergencies based on the binary matrix data constructed by the link creation module;

[0050] The resilience measurement analysis module conducts resilience measurement analysis on the three-stage plan-based airport emergency response network constructed by the emergency response network construction module under emergencies.

[0051] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for analyzing the resilience of an airport emergency response network under an emergency event as described in claim 1.

[0052] The present invention has the following beneficial effects:

[0053] The present invention integrates multi-dimensional operational contents such as subjects, resources, and tasks, uses the meta-network method, constructs an emergency response network model under emergencies for the operational mechanism of airport emergency response, models and evaluates the emergency plan of the airport emergency response network under emergencies from the perspective of the overall system layout, and measures and analyzes the resilience of the airport emergency response network. According to the evaluation results, the deficiencies in the plan can be clarified and further improvements can be made, which is helpful to improve the resilience level of the airport to cope with emergencies and makes up for the deficiencies in the existing resilience analysis of complex airport networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of the airport emergency response network resilience analysis method under emergencies described in the present invention;

[0055] Figure 2 This is the airport emergency response network diagram for emergencies based on the first phase of the plan;

[0056] Figure 3 This is the airport emergency response network diagram for emergencies based on the second phase of the plan;

[0057] Figure 4 This is the airport emergency response network diagram for the third phase of emergencies based on the plan; DETAILED DESCRIPTION

[0058] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0059] Embodiment 1:

[0060] The airport emergency response network resilience analysis method under emergency events described in the present invention is as follows Figure 1 As shown, the process includes the following:

[0061] Step 1: Based on the airport's emergency plan documents, use NVIVO software to identify and determine the four key elements of emergency response before, during, and after an airport emergency: subject (A), resource (R), knowledge (K), and task (T).

[0062] Step 2: Based on the relationship between the key element nodes, create the links between the nodes of the airport emergency response network under emergencies, and describe them using the binary matrix [AA], [AT], [AR], [AK], [RT], [KT];

[0063] Among them, through the adjacency matrix A = {a ij} to indicate the connection status of nodes in the network. If two nodes are connected, then a ij =1; if the two nodes are not connected, then a ij =0;

[0064] Among them, the binary matrix [AA] indicates whether there is an interactive relationship between the subjects in the network, "1" indicates that there is a collaboration between the corresponding subject nodes, and "0" indicates that there is no interactive relationship between the subjects; the binary matrix [AT] indicates that the subject in the network needs to complete a task, "1" indicates that the corresponding subject needs to be responsible for the task corresponding to the column, and "0" indicates that the subject does not undertake the task; the binary matrix [AR] corresponds to the availability between the subject and the resources within the network, "1" represents that the subject corresponding to the resource is accessible, and "0" represents that the subject corresponding to the resource is not accessible; the binary matrix [AK] refers to the availability between the subject and the knowledge within the network, "1" represents that the subject corresponding to the knowledge is accessible, and "0" represents that the subject corresponding to the knowledge is not accessible; the binary matrix [RT] corresponds to the demand relationship between resources and tasks within the network, "1" represents that the corresponding resource is required to complete the corresponding task, and "0" represents that the resource is not required to complete the task; the binary matrix [KT] corresponds to the demand relationship between knowledge and tasks within the network, "1" represents that the corresponding knowledge is required to complete the corresponding task, and "0" represents that the knowledge is not required to complete the task.

[0065] Step 3: Based on the binary matrix established in step 2, import the Organization Risk Analysis (ORA) software to obtain a three-stage airport emergency response network for emergencies based on the plan.

[0066] Step 4: Select several meta-network indicators that are appropriate to the conceptual characteristics of the stages in order to measure the three-stage resilience level of the airport emergency response organization, emergency response tasks, emergency resources and emergency information and their coordinated interaction under emergencies. The specific process is as follows:

[0067] Step 4.1: First stage toughness measurement analysis and calculation:

[0068] This stage is measured by three indicators: "natural connectivity", "overall task completion" and "task resource / knowledge consistency":

[0069] ① Natural connectivity evaluates the structural robustness of the network in the face of failures by measuring the redundancy of alternative paths. As the number of alternative paths increases, stakeholders have more solutions to deal with response tasks, and the resilience of the emergency response network is enhanced:

[0070]

[0071] Robustness refers to the ability of elements and systems to withstand a certain degree of interference without suffering functional loss; AA represents the AA emergency response network, i.e., the emergency response network between subjects; AA represents the binary matrix of the AA emergency response network; λ j (j=1,...,m) represents the eigenvalue of the matrix [AA]; m represents the total number of eigenvalues; R Rob Indicates the robustness of each stage of the network; represents the eigenvalue power with e as the base; the maximum robustness means that when organizations are fully connected and cooperate with each other, G AA The maximum natural connectivity is achieved; while the minimum robustness means that when all stakeholders do not cooperate, G AA Achieve minimum natural connectivity.

[0072] ② Overall task completion represents the percentage of tasks that can be completed by the subject with the required resources and knowledge;

[0073]

[0074] Among them, R OTC Indicates the overall task completion, |T| refers to the total number of tasks that need to be completed; |S RK |The number of tasks that could not be completed based on whether the subject had the necessary resources and knowledge to perform the task;

[0075]

[0076] Where i represents the row in the binary matrix; j represents the column in the binary matrix; N RK is the knowledge / resource gap matrix, which refers to the gap between the knowledge / resources required to complete the task and the knowledge / resources available to the subject; N RK (i,j) is the matrix N RK The element in the i-th row and j-th column; AT is the binary matrix corresponding to the AT network; AT T is the transpose of the matrix [AT]; AR is the binary matrix corresponding to the AR network; AK is the binary matrix corresponding to the AK network; RT is the binary matrix corresponding to the KT network; KT is the binary matrix corresponding to the KT network; [RT KT] T is the transposed matrix of [RT KT].

[0077] ③Task resource / knowledge consistency refers to the amount of resources and knowledge that the subject does not need to complete the task. It can quantify the resource oversupply and knowledge oversupply of the task:

[0078]

[0079] Among them, R TRW Indicates the amount of resources that the subject does not need to complete the task, R TKW represents the amount of knowledge that the subject does not need when completing the task, m represents the total number of rows in the binary matrix, K1 represents the demand relationship between tasks and resources within the network, n represents the total number of columns in the binary matrix, K2 represents the demand relationship between tasks and knowledge within the network, and ~RT T Indicates whether the resource is needed to complete the task within the network; ~KT T Indicates whether the knowledge is needed to complete the task within the network; X(i,j) is the element in the i-th row and j-th column of the matrix X.

[0080] Step 4.2: Second stage toughness measurement analysis and calculation;

[0081] This stage is measured through three indicators: "efficiency", "performance accuracy" and "overall task completion";

[0082] ① Efficiency refers to the extent to which each component in the network contains the minimum links required to maintain a connection:

[0083]

[0084] Penalty=m-n+K

[0085]

[0086] Among them, REF represents efficiency, which refers to the degree to which each component in the network contains the minimum links required to maintain connectivity. Penalty represents the number of unconnected chains in the network. A is a unimodal input network with m edges and n nodes. Let K be the number of elements in A, and k i is the size of component i.

[0087] ②Performance accuracy refers to the degree to which the subject can accurately perform the assigned tasks based on the acquired knowledge and resources:

[0088] Let b be the cardinality of the knowledge node set K, N be the transpose of the matrix [KT], and S be the matrix [AK];

[0089] The correct classification of b with respect to task t is defined as:

[0090]

[0091] The classification of b by subject i with respect to task t is defined as:

[0092]

[0093] The group of agents assigned to task t classifies b using majority voting:

[0094]

[0095] When gans=tans, the tasks are classified and the classification is repeated multiple times for each task;

[0096] Among them, true answer represents the correct classification of subject A regarding b relative to task T; N tk Indicates the availability of tasks and knowledge within the network; b k Indicates the length of a two-dimensional string of length K; R it Indicates that subject i believes that this knowledge is necessary to complete the task; S ij A binary matrix representing subject and knowledge; answer i Indicates the number of correct classifications of b by subject A on task T; gans i represents the group of subjects assigned to task t to classify b using majority voting; |I| represents the number of subjects' classifications of b with respect to task t; k represents the length of the two-dimensional string; i represents the row in the binary matrix.

[0097] ③ Overall task completion refers to the percentage of tasks that can be completed by entities with the required resources and knowledge.

[0098] The emergency response tasks in the second phase mainly involve responding to disasters. The tasks in this phase will lay the foundation for the recovery and reconstruction phase. Therefore, measuring the overall task completion of this phase can help gain a deeper understanding of the resilience level in this phase.

[0099] Step 4.3: Third stage toughness measurement analysis and calculation;

[0100] This stage is measured by three indicators: "average speed", "personnel cost" and "cognitive demand":

[0101] ① Average speed refers to the average speed at which any two (reachable) nodes can interact, which is the inverse of the average shortest path length between node pairs:

[0102]

[0103] Among them, R AS represents the average speed at which any two (reachable) nodes can interact; n represents the number of columns of the binary matrix; i represents the row of the binary matrix; G AA is the AA emergency response network; v is G AA Minimum link value; d i It is the sum of the minimum paths from the main node Ai to all other main nodes;

[0104]

[0105] Where D is defined as G AA distance matrix; if there is a path between node i and node u, then D(i,u) is the shortest path between node i and node u.

[0106] ④ Personnel cost: The cost of a participant is the sum of the number of input links from other participants and the number of output links to knowledge, resource, and task nodes, scaled by dividing by the total number of links to / from nodes that the agent may have.

[0107] ⑤ Cognitive demand: measures the total amount of work each agent spends to complete the task.

[0108] This embodiment also provides an airport emergency response network resilience analysis system under emergency events, including:

[0109] The data acquisition and identification module is used to obtain data from the airport's emergency plan files and identify the four key element nodes of the subject, resources, knowledge, and tasks of emergency response in the three stages before, during, and after an airport emergency occurs.

[0110] The link creation module creates links between nodes based on the key element nodes identified by the data acquisition and identification module, and represents them using a binary matrix.

[0111] The emergency response network construction module constructs a three-stage airport emergency response network for emergencies based on the binary matrix data constructed by the link creation module.

[0112] The resilience measurement analysis module conducts resilience measurement analysis on the three-stage plan-based airport emergency response network constructed by the emergency response network construction module under emergencies.

[0113] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the above-mentioned airport emergency response network resilience analysis method under sudden events are implemented.

[0114] Embodiment 2:

[0115] The airport emergency response network resilience analysis method under emergency events of the present invention comprises the following process:

[0116] Step 1: Based on the airport's emergency plan documents, use NVIVO software to identify and determine the four key elements of the emergency response before, during, and after the airport emergency. The emergency plan documents include the "Emergency Response Law of the People's Republic of China", "Civil Transport Airport Emergency Rescue Management Rules", and "Zhongwei Shapotou Airport Emergency Plan".

[0117] Subject node identification:

[0118] According to the emergency plan documents, the airport emergency response network entities under emergencies include 23 entities, including the Municipal Port and Investment Promotion Office, District People's Government, Emergency Management Bureau, etc. See Table 1 below for details. In Table 1, A01 to A23 represent the numbers of each entity node.

[0119] Table 1 Main nodes of airport emergency response network under emergencies

[0120]

[0121] Resource node identification:

[0122] According to the emergency plan document, 9 resource nodes of the airport emergency response network under emergency events are determined, including emergency disposal material supplies, hotel resources, emergency rescue funds, etc., as shown in Table 2. In Table 2, R01 to R09 represent the numbers of each resource node:

[0123] Table 2 Airport emergency response network resource nodes under emergencies

[0124]

[0125] Knowledge node identification:

[0126] According to the emergency plan document, 10 knowledge nodes of the airport emergency response network under emergencies are determined, including analysis and judgment of various types of early warning information reported, evaluation of the development of the situation, etc., as shown in Table 3. In Table 3, K01 to K10 represent the numbers of each knowledge node:

[0127] Table 3 Main nodes of airport emergency response network under emergencies

[0128]

[0129] Task node identification:

[0130] According to the emergency plan document, the tasks in the emergency response network under the emergency event are analyzed, and the three-stage task nodes are identified, as shown in Tables 4, 5, and 6:

[0131] Table 4 Task nodes of airport emergency response network under emergencies (first phase)

[0132]

[0133]

[0134]

[0135] Table 5 Task nodes of airport emergency response network under emergencies (second stage)

[0136]

[0137]

[0138]

[0139] Table 6 Task nodes of airport emergency response network under emergencies (third stage)

[0140]

[0141]

[0142] Step 2: Based on the relationship between the nodes in the emergency plan file, create the links between the nodes of the airport emergency response network under the emergency, and use the binary matrix [AA], [AT], [AR], [AK], [RT], [KT] to describe it. Examples are shown in Tables 7 and 8 below:

[0143] Table 7 Part of the binary matrix establishment process

[0144]

[0145] Table 8 Example of the second stage [AT] matrix

[0146]

[0147]

[0148] Step 3: Based on the binary matrix established in step 2, the Organization Risk Analysis (ORA) software is used to obtain the three-stage airport emergency response network under emergency plans, such as Figure 2 , Figure 3 , Figure 4 As shown, Figure 2 , Figure 3 , Figure 4 In the model, Agent represents the subject, Knowledge represents the resource, Resource represents the knowledge, and Task represents the task.

[0149] Step 4: Select the three-stage index of the meta-network in Example 1 to measure the three-stage resilience level of the airport emergency response organization, emergency response tasks, emergency resources and emergency information and their coordinated interaction under emergencies;

[0150] (1) Measurement of resilience level in the first stage:

[0151] The overall task completion of the airport emergency response network under emergencies based on the emergency plan documents is 0.550, which is at an upper-middle level, indicating that the system's response capability is at an upper-middle level; the network's task resource / knowledge consistency is 0.716, which is at an upper level, indicating that the resources and knowledge of the emergency response are sufficient, and the efficiency and effect of the emergency response are good.

[0152] (2) Second stage resilience level measurement:

[0153] The efficiency of the airport emergency response network under emergencies based on the emergency plan documents is 0.844, reflecting the fast execution speed of tasks in the emergency response network; the performance accuracy is 0.263, reflecting the degree to which the subject can accurately execute the assigned tasks according to the speed at which it acquires knowledge and resources; the overall task completion is 0.536, reflecting that the overall response level of the system is above average.

[0154] (3) Measurement of resilience level in the third stage:

[0155] The personnel cost in the airport emergency response network under emergencies based on the emergency plan document is 0.145, reflecting that the personnel cost in emergency response is relatively low; the network cognitive demand based on the plan is 0.144, which is relatively low, so the communication and collaboration among various subjects need to be strengthened in the improvement of the plan.

[0156] The embodiments are preferred implementations of the present invention, but the present invention is not limited to the above-mentioned implementations. Any obvious improvements, substitutions or modifications that can be made by those skilled in the art without departing from the essential content of the present invention belong to the protection scope of the present invention.

Claims

1. A method for analyzing the resilience of an airport emergency response network under emergencies, characterized in that: The process includes the following: Step 1: Identify the key elements of emergency response in the three stages before, during and after an airport emergency, including: subject (A), resource (R), knowledge (K), and task (T); Step 2: Based on the relationship between the key element nodes, create the links between the nodes of the airport emergency response network under the emergency, using a binary matrix representation, including [AA], [AT], [AR], [AK], [RT], [KT]; Step 3: Based on the binary matrix, construct the airport emergency response network under emergencies; Step 4: Conduct a three-stage network resilience measurement analysis.

2. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 1 is characterized in that: In step 4, in the first stage of resilience measurement analysis, three indicators are used for measurement: natural connectivity, overall task completion, and task resource / knowledge consistency; In the second stage of resilience measurement analysis, three indicators, efficiency, performance accuracy, and overall task completion, were used for measurement; In the third stage of resilience measurement analysis, three indicators are used for measurement: average speed, personnel cost, and cognitive demand.

3. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: The natural connectivity evaluates the structural robustness of the network in the face of failures by measuring the redundancy of alternative paths: Robustness refers to the ability of elements and systems to withstand a certain degree of interference without suffering functional loss; AA represents the AA emergency response network; AA represents the binary matrix of the AA emergency response network; λ j (j=1,...,m) represents the eigenvalue of the matrix [AA]; m represents the total number of eigenvalues; R Rob Indicates the robustness of each stage of the network; represents the eigenvalue power with e as the base; the maximum robustness means that when organizations are fully connected and cooperate with each other, G AA The maximum natural connectivity is achieved; while the minimum robustness means that when all stakeholders do not cooperate, G AA Achieve minimum natural connectivity.

4. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: The overall task completion represents the percentage of tasks that can be completed by a subject with the required resources and knowledge; Among them, R oTC Indicates the overall task completion, |T| refers to the total number of tasks that need to be completed; |S RK |The number of tasks that could not be completed based on whether the subject had the necessary resources and knowledge to perform the task; Where i represents the row in the binary matrix; j represents the column in the binary matrix; N RK is the knowledge / resource gap matrix, which refers to the gap between the knowledge / resources required to complete the task and the knowledge / resources available to the subject; N RK (i, j) is the matrix N RK The element in the i-th row and j-th column; AT is the binary matrix corresponding to the AT network; AT T is the transpose of the matrix [AT]; AR is the binary matrix corresponding to the AR network; AK is the binary matrix corresponding to the AK network; RT is the binary matrix corresponding to the KT network; KT is the binary matrix corresponding to the KT network; [RT KT] T is the transposed matrix of [RT KT].

5. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: The task resource / knowledge consistency refers to the amount of resources and knowledge that the subject does not need to complete the task: Among them, R TRW Indicates the amount of resources that the subject does not need to complete the task, R TKW represents the amount of knowledge that the subject does not need when completing the task, m represents the total number of rows in the binary matrix, K1 represents the demand relationship between tasks and resources within the network, n represents the total number of columns in the binary matrix, K2 represents the demand relationship between tasks and knowledge within the network, and ~RT T Indicates whether the resource is needed to complete the task within the network; ~KT T Indicates whether the knowledge is needed to complete the task within the network; X(i, j) is the element in the i-th row and j-th column of the matrix X.

6. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: Efficiency refers to the degree to which each component in the network contains the minimum links required to maintain connectivity: Penalty=m-n+K Among them, R EF represents efficiency, which refers to the degree to which each component in the network contains the minimum links required to maintain connectivity. Penalty represents the number of unconnected chains in the network. A is a unimodal input network with m edges and n nodes. Let K be the number of elements in A, and k i is the size of component i.

7. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: The performance accuracy is to measure the degree to which the subject can accurately perform the assigned tasks based on the acquired knowledge and resources: Let b be the cardinality of the knowledge node set K, N be the transpose of the matrix [KT], and S be the matrix [AK]; The correct classification of b with respect to task t is defined as: The classification of b by subject i with respect to task t is defined as: The group of agents assigned to task t classifies b using majority voting: When gans=tans, the tasks are classified and the classification is repeated multiple times for each task; Among them, true answer represents the correct classification of subject A regarding b relative to task T; N tk Indicates the availability of tasks and knowledge within the network; b k Indicates the length of a two-dimensional string of length K; R it Indicates that subject i believes that this knowledge is necessary to complete the task; S ij A binary matrix representing subject and knowledge; answer i Indicates the number of correct classifications of b by subject A on task T; gans i represents the group of subjects assigned to task t to classify b using majority voting; |I| represents the number of subjects' classifications of b with respect to task t; k represents the length of the two-dimensional string; i represents the row in the binary matrix.

8. The method for analyzing the resilience of an airport emergency response network under an emergency according to claim 2 is characterized in that: The average speed is the average speed at which any two nodes can interact: Among them, R AS represents the average speed at which any two nodes can interact; n represents the number of columns of the binary matrix; i represents the row of the binary matrix; G AA It is the AA emergency response network; i is the minimum path sum: Where D is G AA distance matrix; if there is a path between node i and node u, then D(i,u) is the shortest path between node i and node u.

9. A system for implementing the airport emergency response network resilience analysis method under emergency events as described in claim 1, characterized in that: include: The data acquisition and identification module is used to obtain data from the airport's emergency plan files and identify and obtain the four key elements of the subject, resource, knowledge, and task of emergency response in the three stages before, during, and after an airport emergency occurs; The link creation module creates links between nodes based on the key element nodes identified by the data acquisition and identification module, and represents them using a binary matrix; The emergency response network construction module builds a three-stage airport emergency response network for emergencies based on the binary matrix data constructed by the link creation module; The resilience measurement analysis module conducts resilience measurement analysis on the three-stage plan-based airport emergency response network constructed by the emergency response network construction module under emergencies.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for analyzing the resilience of an airport emergency response network under emergencies described in claim 1.

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