Complex system elasticity evaluation method and device, medium and product

Abstract

The invention discloses a complex system elasticity evaluation method and device, a medium and a product, and relates to the technical field of complex systems and reliability, and the method comprises the steps: setting an external damage strategy and an external damage type of a complex system, and carrying out the external damage injection of the complex system, obtaining a change value of a state variable of the complex system and a change value of an external damage input variable in a preset time period; according to the complex system convolution model, the change value of the state variable in the preset time period and the change value of the external damage input variable, the change value of the elastic function of the complex system in the preset time period is obtained through calculation, and then the elastic evaluation value of the complex system is determined. According to the method, the complex system is subjected to elasticity evaluation by combining the system performance and the external damage, the accuracy of the elasticity evaluation of the complex system is effectively improved, and meanwhile, the application range of the elasticity evaluation of the complex system is expanded.

Description

Technical Field

[0001] The present application relates to the field of complex systems and reliability technology, and in particular to a complex system resilience assessment method, equipment, medium and product. Background Art

[0002] A complex system is a system composed of many interacting members. These components usually have interactive relationships such as dependence, conflict, and cooperation. The complexity of these relationships makes the system show different behaviors and changes, and also makes the analysis of the system go beyond the dimension of ordinary systems. In the context of today's scientific and technological and social development, the structure of matter and energy controlled by humans is becoming increasingly large, and complex systems have become a universal form of connection between things, such as urban systems, equipment systems, and transportation systems. There are a wide range of individual behaviors, collaborative behaviors between individuals, and collective intelligent behaviors in complex systems. These behaviors give complex systems the characteristics of self-organization, self-adaptation, and self-recovery. However, due to the existence of complex dependencies, conflicts, and cooperative interactions in complex systems, these behaviors make complex systems extremely vulnerable when facing destructive events. Once disturbances or damage occur, complex systems are prone to cascading failures, which greatly reduces their survivability. Complex system research has now become a hot spot and frontier in artificial intelligence and complex system research. It is not only conducive to explaining and understanding the emerging intelligent characteristics and evolution laws of complex groups in natural society, but also helps to solve technical difficulties in engineering, military and other fields, and provides further innovations in theories and methods for research frontiers such as artificial intelligence and swarm intelligence.

[0003] System resilience is a comprehensive concept derived from concepts such as security and reliability for post-disturbance recovery. It is defined as the ability of a system to absorb and resist the impact of damage and recover when it is damaged. Adaptation, robustness, and recovery are the key elements that distinguish resilience from other concepts. Resilience theory is being applied to different fields, such as psychology, economics, and engineering. Conducting analytical and evaluation research on the resilience of complex systems has far-reaching significance and impact on improving the survival and rapid recovery capabilities of complex systems in the face of complex and changing tasks, unknown and uncertain environments, and extreme conditions or deliberate attacks. It is becoming an increasingly important part of complex system research. Existing resilience evaluation methods are based on the perspective of complex system performance changes, considering the time domain characteristics or related function characteristics of state responses, and evaluating and analyzing complex system resilience from the perspective of complex system performance. However, the existing resilience evaluation methods have limitations such as low accuracy and low applicability. Summary of the invention

[0004] The applicant's research found that changes in the performance of a complex system not only depend on the inherent elastic mechanism of the complex system itself, but also are related to external disturbances or damage to the complex system. In view of this, the present invention provides a complex system elasticity assessment method, equipment, medium and product. By combining the performance of the complex system and external damage to conduct elasticity assessment on the complex system, the accuracy of the elasticity assessment of the complex system can be effectively improved, while expanding the scope of application of the elasticity assessment of the complex system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a complex system resilience assessment method, comprising:

[0007] Setting an external destruction strategy and external destruction type for a complex system; the external destruction strategy is a strategy for randomly causing nodes in the complex system to enter a fault state according to a certain probability distribution; the node is a basic unit in the complex system;

[0008] According to the external destruction strategy and the external destruction type, external destruction is injected into the complex system to obtain the change value of the state variable of the complex system and the change value of the external destruction input variable within a preset time period; wherein the preset time period is the time from the start of external destruction injection to the time when the complex system returns to a balanced state after elastic recovery; the state variable is a variable representing the performance state of the complex system; the external destruction input variable is a variable representing the interference of the external destruction on the complex system; the external destruction input variable is determined according to the external destruction type;

[0009] According to the complex system convolution model, the change value of the state variable within the preset time period and the change value of the external damage input variable within the preset time period, the change value of the elasticity function of the complex system within the preset time period is calculated; the complex system convolution model is a model that represents that the change amount of the complex system state variable is equal to the convolution of the external damage input variable and the elasticity function;

[0010] The elasticity evaluation value of the complex system is determined according to the change value of the elasticity function of the complex system within the preset time period.

[0011] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the complex system resilience assessment method described in the first aspect.

[0012] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the complex system resilience assessment method described in the first aspect.

[0013] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the complex system resilience assessment method described in the first aspect.

[0014] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0015] The present application provides a complex system resilience assessment method, equipment, medium and product. The present application establishes the connection between the system state change of the complex system and the external damage input and the system resilience through the complex system convolution model. Then, in the process of complex system resilience assessment, the complex system is injected with external damage according to the set external damage strategy and external damage type, and the change values ​​of the state variables within a preset time period and the change values ​​of the external damage input variables are collected. Then, according to the complex system convolution model, the change values ​​of the state variables within the preset time period and the change values ​​of the external damage input variables within the preset time period, the change value of the elasticity function of the complex system within the preset time period is calculated, and according to the change value of the elasticity function of the complex system within the preset time period, the elasticity assessment value of the complex system is determined, thereby realizing the resilience assessment of the complex system in combination with system performance and external damage, effectively improving the accuracy of the resilience assessment of the complex system, and expanding the scope of application of the resilience assessment of the complex system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A flowchart of a complex system elasticity assessment method provided in one embodiment of the present application;

[0018] Figure 2 A flowchart of a process for determining a state variable provided in an embodiment of the present application;

[0019] Figure 3 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0021] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0022] In an exemplary embodiment, Figure 1 As shown, a complex system resilience assessment method is provided, including the following steps 101 to 104. Among them:

[0023] Step 101, setting an external destruction strategy and external destruction type for a complex system; the external destruction strategy is a strategy for randomly causing nodes in the complex system to enter a fault state according to a certain probability distribution; the node is a basic unit in the complex system.

[0024] External damage represents the impact of the external environment on the system state. For complex systems, when natural disasters, natural interference, enemy attacks and other external damages affect the system, the system state will be degraded to a certain extent. System resilience is based on the destruction of complex systems. Only when complex systems are affected by external damage can system resilience be truly manifested.

[0025] In an exemplary embodiment, the certain probability distribution is determined based on historical failure data of the complex system.

[0026] In other words, the external destruction strategy (random node destruction strategy) refers to the individual failures caused by random failures of individuals (basic units) in complex systems or random attacks by external factors, and follows a certain probability distribution. When analyzing and simulating such forms of destruction, historical failure data should be referred to to improve the accuracy of distribution and parameters, and exponential distribution can usually be used instead.

[0027] In an exemplary embodiment, the external destruction strategy is reflected in the network model as follows: randomly selecting network nodes and their edges for destruction according to probability distribution, so that the nodes enter a redundant (backup) or faulty state. If the node is in a faulty state, the edges between the node and other nodes can be disconnected.

[0028] Step 102, inject external destruction into the complex system according to the external destruction strategy and the external destruction type, and obtain the change value of the state variable of the complex system and the change value of the external destruction input variable within a preset time period; wherein the preset time period is the time from the start of external destruction injection to the time when the complex system returns to a balanced state after elastic recovery; the state variable is a variable representing the performance state of the complex system; the external destruction input variable is a variable representing the interference of the external destruction on the complex system; the external destruction input variable is determined according to the external destruction type.

[0029] In this application, the state variables of a complex system are a set of variables used to characterize the internal behavior of the complex system. The following takes a certain drone complex system as an example to explain the process of determining the state variables of the complex system. The drone complex system contains 100 drones, which interact with each other through wireless communication modes to form an interactive communication network. In this example, the state variables are used as a description and characterization of the current network communication function completion status of the drone complex system. Therefore, the network performance parameters are used as the state variables of the complex system. Specifically, Figure 2 is a flow chart of the process of determining the state variables in this embodiment, such as Figure 2 As shown, the determination process specifically includes the following steps:

[0030] Step 201, analyzing the basic units and interaction relationships of the complex system.

[0031] In this example, the basic components of a certain UAV complex system and the interaction relationship between the units are analyzed, including the number of UAVs, the communication performance of a single UAV, and the communication relationship between UAVs. Together, they constitute a system structure description of the complex system and provide system information for the abstraction of the complex system network model, which is used to support the acquisition of performance indicators of the UAV complex system network model.

[0032] Step 202: Establish a network model of the complex system.

[0033] In this embodiment, the complex system of the UAV has obvious network characteristics. Based on the complex system structure description obtained by the analysis in step 201, the complex system of the UAV is abstracted into a network model including a point set and an edge set. As an optional implementation method, the complex system network model can be represented as a five-tuple G = (K, L, F) of a node set, a connection set, a node attribute, a connection attribute, and a community. K ,F L ,P), where

[0034] K={n1,n1,…n N} is the node set of G, where nodes represent the basic units in the complex system network, and N is the number of nodes in G;

[0035] L=[l ij ] is the connection set or edge set of G, which represents the interaction relationship (connection relationship) between the nodes of the complex system network. ij Represents node n i and node n j The connection relationship between nodes in a complex system network can be represented by an adjacency matrix;

[0036] is the attribute set of the node set K, It represents node n i The attributes it has, is node n i The j-th attribute value of , such as node type, node load, node importance, etc.;

[0037] is the attribute set of the connection set L, It means l ij The properties it has, Yes ij The r,r∈{1,2,...,z}th attribute value of , such as wired or wireless connection, connection type, connection distance, etc.;

[0038] P={P1,P2,...,P V} is the community set in G, which represents the set of nodes and edges decomposed due to different tasks or attributes in a heterogeneous complex network.

[0039] Step 203: Use the network model performance index as a complex system state variable.

[0040] In this embodiment, based on the network model topology, the communication performance of the UAV complex system is used as a state variable. The communication performance is an indicator for measuring the communication rate of the UAV complex system. The communication performance p(t) of the UAV complex system is calculated as follows:

[0041]

[0042] Among them, d i,j (t) represents the topological distance from node i to node j in the complex system network at time t; N is the total number of nodes in the network. That is, the communication performance of the complex system of the UAV is the inverse of the topological distance.

[0043] In addition, for other complex systems, such as large-scale power grid complex systems, the traffic entropy E of nodes and edges is used as a physical indicator to characterize its state variables, and its calculation formula is as follows:

[0044]

[0045] Where k represents the node or edge in the network corresponding to the large-scale complex power grid system; I k Represents the flow of node or edge k; nodes include power generation buses, transmission buses, distribution buses, substations and transformers in large-scale complex power grid systems; edges represent the connection lines (transmission cables) between nodes.

[0046] For complex systems of equipment systems, the total number of combat loops is used as a physical indicator to characterize its state variables. The calculation formula is as follows:

[0047]

[0048] Among them, S k represents the total number of combat loops of length k; k represents the number of edges in the combat loop; the combat loop network of equipment complex system can be represented by the adjacency matrix A to represent the connection relationship of its edges, and the element It represents the number of loops (combat loops) of length k passing through node i in the adjacency matrix A; the node represents the (weapon) equipment in the complex system of the equipment system; the edge represents the communication interaction relationship between nodes.

[0049] In this application, the external damage input variable is determined according to the external damage type. The external damage input variable can represent the change of the state variable of the complex system under the destruction strategy only, or the influence (interference) of the external damage on the state variable of the complex system. Different damage situations or types have different functional forms of the external damage input variable.

[0050] In an exemplary embodiment, when the external damage type is single damage, the expression of the external damage input variable is:

[0051]

[0052] Where d(t) represents the external damage input variable; t represents the independent variable time; δ(t) is the unit pulse function; H is the coefficient of the unit pulse function δ(t); t e is the injection moment of external damage; ε is the duration of external damage, which is a minimum value approaching 0.

[0053] That is, if the external damage is a single damage, that is, the damage is only performed once, the external damage input variable d(t) is constructed as an impulse function.

[0054] In an exemplary embodiment, when the external damage type is multiple continuous stable damage, the expression of the external damage input variable is:

[0055]

[0056] Where d(t) represents the external damage input variable; t represents the independent variable time; u(t) is the unit step function, p d is the coefficient of the unit step function u(t); t e A moment of injection for external destruction.

[0057] That is, if the external damage is multiple continuous stable damages, that is, damage is carried out at intervals and the degree of damage is the same (such as the number of fault nodes generated by each damage is the same), then the external damage input variable d(t) is constructed as a step function.

[0058] In an exemplary embodiment, when the external damage type is multiple continuous growth damage, the expression of the external damage input variable is:

[0059]

[0060] Where d(t) represents the external damage input variable; t represents the independent variable time; λ(t) is the unit ramp function; v d is the coefficient of the unit ramp function λ(t); t e A moment of injection for external destruction.

[0061] That is, if the external damage is multiple continuous growth damages, that is, damage is carried out at intervals and the degree of damage increases (such as each damage produces more fault nodes than the previous one), then the external damage input variable d(t) is constructed as a ramp function.

[0062] In addition, those skilled in the art can determine the type of destructive input according to actual conditions. The destructive impact can not only be modeled as a linear and continuous signal function, but also, for situations where the changes in the destructive input are more complex, the actual data can be comprehensively considered to abstract it into more complex nonlinear and discrete signals.

[0063] Step 103, based on the complex system convolution model, the change value of the state variable within the preset time period and the change value of the external destructive input variable within the preset time period, calculate the change value of the elasticity function of the complex system within the preset time period; the complex system convolution model is a model that represents that the change amount of the state variable of the complex system is equal to the convolution of the external destructive input variable and the elasticity function.

[0064] In this application, external damage is defined as the input of the system. The input causes the change of the state of the complex system. The change characteristics of the state caused by the input, such as "resistance, absorption, and recovery", can be regarded as the elasticity of the system. Therefore, the elasticity of the complex system is modeled as a transfer function R(s) between input and state using the following formula:

[0065] P(s) = R(s) × D(s);

[0066] Among them, P(s) represents the state of the complex system in the complex domain; R(s) represents the elasticity of the complex system in the complex domain; D(s) represents the external destructive input of the complex system in the complex domain.

[0067] Furthermore, the time domain functional relationship between the state response, external damage and elasticity of the complex system is derived, namely the convolution model:

[0068]

[0069] Among them, ▽p(t) is the change (decrease) of the state variable of the complex system, p(t) represents the state variable of the complex system; p0 represents the initial state variable value of the complex system; t represents the independent variable time; r(t) represents the elasticity function of the complex system; d(t) represents the external destructive input variable of the complex system; the symbol * represents the convolution operation.

[0070] Based on the above convolution model, the elasticity function of the following complex system can be obtained:

[0071] (1) If d(t) is an impulse function, the elasticity function is:

[0072] r(t)=p0-p(t);

[0073] (2) If d(t) is a step function, the elasticity function is:

[0074]

[0075] (3) If d(t) is a ramp function, the elasticity function is:

[0076]

[0077] (4) If d(t) is not the case above, according to the convolution theorem, that is, the product of the Fourier transforms of two functions is equal to their convolved Fourier transforms, and through the inverse Fourier transform, the elastic function r(t) is obtained,

[0078]

[0079] Where F(p(t)) represents the Fourier transform of the state variable p(t); F(d(t)) represents the Fourier transform of the corrupted input variable d(t); -1 (·) represents inverse Fourier transform.

[0080] That is, when the damage input variable d(t) and the state variable p(t) are known, the elasticity function can be obtained.

[0081] Step 104 : determining an elasticity evaluation value of the complex system according to a change value of the elasticity function of the complex system within the preset time period.

[0082] In an exemplary embodiment, step 104 specifically includes:

[0083] An average operation is performed on the change values ​​of the elasticity function of the complex system within the preset time period to obtain the elasticity evaluation value of the complex system.

[0084] In this embodiment, the elasticity of the complex system is evaluated by the following formula:

[0085]

[0086] Among them, I is the elasticity index of the complex system; r(t) is the elasticity function of the complex system; t e Inject moments into external destruction; t f is the moment when the complex system recovers to equilibrium after elasticity; r i is the discrete value of the elasticity function, n is the discrete value of the elasticity function r i The number of .

[0087] The method proposed in this application is further explained below by taking a certain UAV complex system as an example. In this case, a node in the complex network of the UAV is randomly selected for destruction at each unit time interval, and its edges with adjacent nodes are removed, and this destruction lasts for a certain period of time, that is, the destruction type is multiple continuous stable destructions (the destruction input variable is constructed as a step function). Inject external destruction into the complex system in the above manner, and monitor the change values ​​of the state variables and the destruction input variables of the complex system of the UAV. Assume that the coefficient p of the destruction input variable d =1.

[0088] The discrete function value of the external damage input function d(t) at the unit time acquisition frequency is shown in Table 1.

[0089] Table 1 Discrete function value table of external damage input

[0090]

[0091]

[0092] Under the random node destruction strategy, the trend of state variables that measure the network communication performance of the complex system is monitored by software or hardware at fixed intervals until the destruction strategy ends and the state variables are restored to a certain extent and remain unchanged. The values ​​of all state variables from before the destruction strategy starts to after the state variables are restored to remain unchanged are summarized for elasticity analysis. In this embodiment, the discrete values ​​of the complex system state variables are shown in Table 2.

[0093] Table 2 Discrete value table of complex system state variables

[0094] t p 0 1 1 1 2 1 3 0.996711 4 0.966294 5 0.939627 6 0.916248 7 0.895751 8 0.877781 9 0.862027 10 0.848215 11 0.836106 12 0.82549 13 0.816183 14 0.808023 15 0.80087 16 0.794598 17 0.7891 18 0.784279 19 0.780053 20 0.776348

[0095] It is understandable that the above-mentioned complex system performance parameters are only an example provided in the embodiment of the present application, and those skilled in the art may select other performance parameters to perform elasticity evaluation and verification according to actual conditions.

[0096] Based on the system performance (state variables) and the system's external impact (external damage input variables) data in Tables 1 and 2, the discrete values ​​of the elasticity function can be obtained, as shown in Table 3:

[0097] Table 3 Discrete value table of elasticity function

[0098] t r 0 0 1 0 2 0 3 0.28542 4 0.25023 5 0.21938 6 0.19233 7 0.16862 8 0.14783 9 0.1296 10 0.11363 11 0.09962 12 0.08733 13 0.07657 14 0.06713 15 0.05885 16 0.0516 17 0.04523 18 0.03966 19 0.03477 20 0.03048

[0099] Based on the elasticity function data in Table 3, it can be calculated that the elasticity evaluation value of the UAV complex system is 0.1166.

[0100] The present application also provides an application scenario, and the application scenario applies the above-mentioned complex system elasticity assessment method. Specifically: the complex system elasticity assessment method provided in this embodiment can be applied in the scenario of complex system elasticity assessment.

[0101] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for related data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a complex system resilience assessment method is implemented.

[0102] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0103] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0104] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0106] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0107] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0108] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0109] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A complex system resilience assessment method, characterized in that: The complex system resilience assessment method comprises: Setting an external destruction strategy and external destruction type for a complex system; the external destruction strategy is a strategy for randomly causing nodes in the complex system to enter a fault state according to a certain probability distribution; the node is a basic unit in the complex system; According to the external destruction strategy and the external destruction type, external destruction is injected into the complex system to obtain the change value of the state variable of the complex system and the change value of the external destruction input variable within a preset time period; wherein the preset time period is the time from the start of external destruction injection to the time when the complex system returns to a balanced state after elastic recovery; the state variable is a variable representing the performance state of the complex system; the external destruction input variable is a variable representing the interference of the external destruction on the complex system; the external destruction input variable is determined according to the external destruction type; According to the complex system convolution model, the change value of the state variable within the preset time period and the change value of the external damage input variable within the preset time period, the change value of the elasticity function of the complex system within the preset time period is calculated; the complex system convolution model is a model that represents that the change amount of the complex system state variable is equal to the convolution of the external damage input variable and the elasticity function; The elasticity evaluation value of the complex system is determined according to the change value of the elasticity function of the complex system within the preset time period.

2. The complex system resilience assessment method according to claim 1, characterized in that: The expression of the complex system convolution model is: p0-p(t)=r(t)*d(t); Among them, p(t) represents the state variable of the complex system; t represents the independent variable time; p0 represents the initial state variable value of the complex system; r(t) represents the elasticity function of the complex system; d(t) represents the external destructive input variable of the complex system; the symbol * represents the convolution operation.

3. The complex system resilience assessment method according to claim 1, characterized in that: When the external damage type is single damage, the expression of the external damage input variable is: Where d(t) represents the external damage input variable; t represents the independent variable time; δ(t) is the unit pulse function; H is the coefficient of the unit pulse function δ(t); t e is the injection time of external damage; ε is the duration of external damage.

4. The complex system resilience assessment method according to claim 1, characterized in that: When the external damage type is multiple continuous stable damage, the expression of the external damage input variable is: Where d(t) represents the external damage input variable; t represents the independent variable time; u(t) is the unit step function, p d is the coefficient of the unit step function u(t); t e A moment of injection for external destruction.

5. The complex system resilience assessment method according to claim 1, characterized in that: When the external damage type is multiple continuous growth damage, the expression of the external damage input variable is: Where d(t) represents the external damage input variable; t represents the independent variable time; λ(t) is the unit ramp function; v d is the coefficient of the unit ramp function λ(t); t e A moment of injection for external destruction.

6. The complex system resilience assessment method according to claim 1, characterized in that: Determining the elasticity evaluation value of the complex system according to the change value of the elasticity function of the complex system within the preset time period specifically includes: An average operation is performed on the elasticity function change value of the complex system within the preset time period to obtain the elasticity evaluation value of the complex system.

7. The complex system resilience assessment method according to claim 1, characterized in that: The certain probability distribution is determined based on historical failure data of the complex system.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the complex system resilience assessment method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the complex system resilience assessment method described in any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the complex system resilience assessment method described in any one of claims 1 to 7 is implemented.

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