Method, system and device for evaluating economic impact of multi-system coupling failure on urban industrial chain

Abstract

The application provides a method, system and device for evaluating the economic influence of multi-system coupling failure on urban industrial chains, comprising the following steps: inputting the basic data of a city to be evaluated into a preset multi-system coupling failure model for function analysis, constructing an industrial correlation graph between different industrial chains in the city to be evaluated, generating real-time fund flow characteristics corresponding to each industrial chain in combination with real-time financial data of the city to be evaluated, respectively constructing an economic transmission path corresponding to each industrial chain, identifying a link breakpoint, predicting the economic transmission path of the link breakpoint by using a time sequence neural network, combining the direct / indirect economic loss of the link breakpoint in the industrial correlation graph, inputting the economic loss value caused by each path breakpoint into the preset multi-system coupling failure model, and performing alarm work in the corresponding city to be evaluated when the economic loss value exceeds a specified loss threshold, thereby providing scientific and timely support for risk prevention and control and emergency decision-making of urban industrial chains and ensuring stable operation of urban industrial chains.

Description

Technical Field

[0001] This invention relates to the field of urban economic security and industrial chain risk assessment technology, and in particular to methods, systems and devices for assessing the economic impact of multi-system coupling failures on urban industrial chains. Background Technology

[0002] With the acceleration of urbanization and the deep integration of global industrial chains, urban industrial chains have become the core carriers supporting urban economic development. However, urban systems are complex coupled systems composed of multiple subsystems such as transportation, energy, communication, and finance. The failure of any subsystem can spread to other systems through the "coupling effect." For example, traffic disruptions caused by extreme weather, production stagnation caused by energy shortages, and logistical disruptions caused by public health events can all cause a chain reaction of impacts on urban industrial chains, leading to serious economic losses. Existing technologies for assessing the economic impact of urban industrial chains often focus on the failure of a single system or a single link in the industrial chain, which has the following shortcomings: Ignoring the multi-system coupling effect: There are strong dependencies between various systems in a city. The failure of a single system may trigger a chain reaction of failures in multiple systems, which in turn will have a wider impact on the industrial chain. However, existing methods do not consider this "system-system-industrial chain" coupling transmission path. Inaccurate industrial linkage analysis: Existing methods mostly construct industrial linkages based on static input-output tables, which cannot reflect the dynamic changes in the upstream and downstream of the industrial chain in real time, resulting in inaccurate identification of the transmission path of impacts on the industrial chain; Lagging economic loss prediction: Existing methods mostly use historical data to fit models to predict economic losses, which makes it difficult to capture the nonlinear and sudden characteristics of economic losses under the failure of multiple systems coupled together, resulting in lagging prediction results and failing to meet the needs of real-time early warning. Lack of a closed-loop early warning mechanism: Existing methods can only calculate economic loss values, but have not established a closed-loop mechanism of "loss calculation - threshold judgment - alarm response", which makes it impossible to trigger emergency measures in a timely manner and difficult to effectively reduce losses; Therefore, this invention provides a method, system, and apparatus for assessing the economic impact of multi-system coupling failures on urban industrial chains. Summary of the Invention

[0003] This invention relates to a method, system, and apparatus for assessing the economic impact of multi-system coupling failures on urban industrial chains. By integrating technologies such as multi-system coupling failure analysis, industrial correlation mapping construction, and temporal neural network prediction, it achieves accurate assessment and risk warning of economic losses in urban industrial chains under multi-system coupling failure scenarios. It is applicable to application scenarios such as urban emergency management, industrial chain planning, and economic risk prevention and control, providing urban managers with a scientific basis for decision-making.

[0004] This invention provides a method for assessing the economic impact of multi-system coupling failures on urban industrial chains, including: Step 1: Input the basic urban data of the city to be evaluated into the preset multi-system coupling failure model for functional analysis, and construct the industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results; Step 2: Using the industry association map and the real-time financial data of the city to be valued, generate real-time capital flow characteristics for each of the industrial chains, and construct the economic transmission path for each of the industrial chains respectively; Step 3: Identify the link interruption points contained in the economic transmission path, use a time-series neural network to predict the economic transmission path of the link interruption points, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. Step 4: Input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and trigger an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

[0005] In one feasible approach Step 1 includes: Step 11: Obtain several basic data points of the city to be estimated, identify the data attributes corresponding to each basic data point of the city, and perform feature enhancement processing on each basic data point of the city to obtain the basic data features corresponding to each basic data point of the city. Step 12: Divide the basic urban data into dynamic data class and static data class according to the data attributes, construct the dynamic data function and static data function of the city to be estimated by combining the basic data characteristics corresponding to each basic urban data, and assign a corresponding analysis model layer to each basic urban data. Step 13: Input the basic data of each city into the preset multi-system coupling failure model, and perform functional analysis on the basic data of the city in each analysis model layer to obtain several dynamic coupling failure output results and several static coupling failure output results of the city to be estimated. Step 14: Based on the basic data of each city, deduce the industrial chain of the city to be estimated, and use the basic data characteristics corresponding to the basic data of each city to combine the dynamic coupling failure output result and the static coupling failure output result to obtain the interaction information between different industrial chains and generate an industrial association map.

[0006] In one feasible approach Also includes: Based on the industry association map, construct and determine several related dynamic coupling failure output results and several related static coupling failure output results for each of the industry chains, and construct dynamic execution functions and static execution functions for each of the industry chains. The dynamic effectiveness of the dynamic execution function and the static effectiveness of the static execution function are analyzed based on the industrial execution process corresponding to each of the aforementioned industrial chains. Based on the dynamic functional effectiveness and the static functional effectiveness, several functional failure information corresponding to the industrial chain are derived, and a failure report for each industrial chain is generated and displayed.

[0007] In one feasible approach Step 2 includes: Step 21: Determine several financial flow items corresponding to each of the industrial chains based on the industrial association map, and obtain the flow characteristics corresponding to each of the financial flow items. Obtain the real-time financial data of the city to be valued, and sample the real-time financial data according to the flow characteristics to obtain several financial data of each of the industrial chains. Step 22: Locate the associated financial data corresponding to each financial data in the industry association map, construct the capital flow process of each industry chain by combining the financial flow items corresponding to each financial data, identify the data value corresponding to each financial data, and construct the real-time capital flow characteristics corresponding to the industry chain based on the data value and the capital flow process. Step 23: Construct several capital chains in the industrial chain based on the real-time capital flow characteristics and capital flow process corresponding to each industrial chain, determine the capital interaction relationship between different industrial chains, and trace the capital chains by combining the capital flow direction corresponding to each financial flow item. Step 24: Based on the capital flow situation corresponding to each capital chain and the capital interaction relationship between different industrial chains, identify the economic expenditure and economic income corresponding to each industrial chain in the industrial association map, and generate the economic transmission path corresponding to each industrial chain.

[0008] In one feasible approach Step 3 includes: Step 31: Divide each of the economic transmission paths into several path links, and construct the economic hash value corresponding to each path link in combination with the industry association map, construct the hash tree corresponding to each economic transmission link, and filter the target path links with interruption characteristics according to the data integrity features corresponding to each branch in the hash tree. Step 32: Analyze the link interruption points corresponding to each target path link in the economic transmission link based on the real-time capital flow characteristics of each industrial chain, and identify several interruption-related links corresponding to each link interruption point in the industrial association map. Step 33: Utilize the temporal neural network to perform structural relationship analysis on each link interruption point and the corresponding interruption-related link, construct an economic graph structure between the link interruption point and the corresponding interruption-related link, and capture the economic information corresponding to each interruption-related link in the economic graph structure based on the interruption economic value corresponding to the link interruption point. Step 34: Locate the target economic information with affected characteristics, and divide the target economic information into directly affected economic information and indirectly affected economic information according to the feature values ​​corresponding to the affected characteristics, and construct the direct / indirect economic losses caused by each link interruption point.

[0009] In one feasible approach Step 4 includes: Step 41: Input the direct / indirect economic losses into the preset multi-system coupling failure model, match the basic urban data and the direct / indirect economic losses in the preset multi-system coupling failure model, and determine several explicit impact characteristics of the city to be estimated; Step 42: Analyze the loss manifestation characteristics of each direct / indirect economic loss in the industrial correlation map in the preset multi-system coupling failure model, and identify the implicit impact characteristics of each loss manifestation characteristic on different economic transmission paths in the industrial correlation map; Step 43: Statistically analyze several explicit impact characteristics and corresponding explicit impact values ​​for each of the economic transmission paths, as well as several implicit impact characteristics and corresponding implicit impact values, to determine the economic loss value corresponding to each of the economic transmission paths. Step 44: Locate emergency economic transmission paths where the economic loss value exceeds the loss threshold, and, in conjunction with the emergency industrial chain corresponding to the emergency economic transmission path, determine the industrial scope corresponding to the emergency industrial chain and issue corresponding alarms.

[0010] In one feasible approach Also includes: When the total value of the explicit impact corresponding to several explicit impact features is greater than the loss threshold, it is determined that an emergency has occurred in the city to be estimated, the emergency impact range corresponding to the emergency is identified, and corresponding alarm work is carried out.

[0011] This invention provides a system for assessing the economic impact of multi-system coupling failures on urban industrial chains, including: The functional analysis module is used to input the basic urban data of the city to be evaluated into a preset multi-system coupling failure model for functional analysis, and to construct an industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results. The economic analysis module is used to generate real-time capital flow characteristics for each of the industrial chains by using the industrial association map and the real-time financial data of the city to be valued, and to construct the economic transmission path for each of the industrial chains respectively. The loss analysis module is used to identify the link interruption points contained in the economic transmission path, predict the economic transmission path of the link interruption points using a time-series neural network, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. The early warning analysis module is used to input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and to issue an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

[0012] This invention provides an assessment device for the economic impact of multi-system coupling failure on urban industrial chains, comprising: the assessment system; It also includes a risk presentation system, which is used to construct and display visual risk information of the city to be assessed based on the economic loss value and the industry association map.

[0013] The beneficial effects achievable by the above technical solution are as follows: In order to provide an assessment method that can consider the failure of multiple systems coupling, accurately identify the transmission path of the industrial chain, predict economic losses in real time, and have a closed-loop early warning function, To fill the gaps in existing technologies and ensure the stable operation of urban industrial chains, this system first uses basic data of the city to be assessed as a foundation. It then constructs an industrial correlation map between different industrial chains by using a pre-set multi-system coupling failure model analysis system. Next, it combines real-time financial data to generate real-time capital flow characteristics for each industrial chain and establishes economic transmission paths. Subsequently, it identifies link breakpoints in these paths, predicts the transmission paths of these breakpoints using a time-series neural network, and analyzes direct and indirect economic losses using the industrial correlation map. Finally, it feeds the loss data back into the model to derive the total loss value at each path breakpoint. If the loss exceeds a specified threshold, an alarm is triggered in the city. This approach fully considers the chain reaction of multi-system coupling failures, dynamically and accurately captures the economic transmission patterns and loss situations of the industrial chain, forming a complete analytical closed loop. It effectively solves the problems of traditional assessments, such as neglecting system coupling, analytical lag, and lack of early warning mechanisms. This provides scientific and timely support for urban industrial chain risk prevention and emergency decision-making, ensuring the stable operation of urban industrial chains.

[0014] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram illustrating the workflow of the method for assessing the economic impact of multi-system coupling failure on urban industrial chains in an embodiment of the present invention. Figure 2 This is a schematic diagram of the composition of the economic impact assessment system for the urban industrial chain caused by the failure of multiple system coupling in an embodiment of the present invention; Figure 3 This is a schematic diagram of the composition of the economic impact assessment device for the urban industrial chain caused by multi-system coupling failure in an embodiment of the present invention. Detailed Implementation

[0017] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0018] Example 1

[0019] This embodiment provides a method for assessing the economic impact of multi-system coupling failures on urban industrial chains, such as... Figure 1 As shown, it includes: Step 1: Input the basic urban data of the city to be evaluated into the preset multi-system coupling failure model for functional analysis, and construct the industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results; Step 2: Using the industry association map and the real-time financial data of the city to be valued, generate real-time capital flow characteristics for each of the industrial chains, and construct the economic transmission path for each of the industrial chains respectively; Step 3: Identify the link interruption points contained in the economic transmission path, use a time-series neural network to predict the economic transmission path of the link interruption points, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. Step 4: Input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and trigger an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

[0020] In this example, the basic city data represents the data generated by the various industrial chains in the city to be evaluated when they perform their work, as well as the city's construction data. In this example, the coupling failure output result represents the output result after functional analysis of the preset multi-system coupling failure model; In this example, the pre-defined multi-system coupling failure model represents a mathematical model used to analyze the joint failure of multiple subsystems or components in a complex system under interaction. The pre-defined multi-system coupling failure model is a two-layer network model. The upper layer is the infrastructure physical network (covering urban subsystems such as transportation, energy, communication, and finance), and the lower layer is the industrial logical network (covering various industrial chains and upstream and downstream related links in the city). In this example, real-time financial data represents financial-related, real-time updated data for the city to be evaluated; In this example, real-time capital flow characteristics represent the features exhibited when capital flows within the industrial chain; In this example, the economic transmission path represents the path formed by economic expenditures and economic incomes in the industrial chain; In this example, direct / indirect economic loss refers to the economic loss caused to the city under evaluation due to link disruption; In this example, the link interruption point represents the location in the economic transmission path where funding is interrupted; In this example, the loss threshold is set at 0.015% of the total economic value of the city to be estimated.

[0021] The working principle and beneficial effects of the above technical solution are as follows: To fill the gap in existing technology and ensure the stable operation of urban industrial chains, an assessment method that considers multi-system coupling failures, accurately identifies the transmission path of industrial chains, predicts economic losses in real time, and has a closed-loop early warning function is proposed. Based on the basic data of the city to be assessed, the system functions are analyzed by pre-setting a multi-system coupling failure model. Based on this, an industrial correlation map between different industrial chains is constructed. Then, real-time financial data is combined to generate real-time capital flow characteristics of each industrial chain and to build economic transmission paths. Subsequently, the link breakpoints in the paths are identified, and the transmission path of the breakpoints is predicted using a time-series neural network. Direct and indirect economic losses are analyzed in conjunction with the industrial correlation map. Finally, the loss data is fed back into the model to derive the total loss value of the path breakpoints. If the loss exceeds a specified threshold, an alarm is triggered in the city. This approach fully considers the chain effect of multi-system coupling failures, dynamically and accurately captures the economic transmission law and loss situation of the industrial chain, forming a complete analytical closed loop. It effectively solves the problems of traditional assessments, such as ignoring system coupling, analysis lag, and lack of early warning mechanisms. This provides scientific and timely support for urban industrial chain risk prevention and emergency decision-making, ensuring the stable operation of urban industrial chains.

[0022] Example 2

[0023] Based on Example 1, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains, step 1 includes: Step 11: Obtain several basic data points of the city to be estimated, identify the data attributes corresponding to each basic data point of the city, and perform feature enhancement processing on each basic data point of the city to obtain the basic data features corresponding to each basic data point of the city. Step 12: Divide the basic urban data into dynamic data class and static data class according to the data attributes, construct the dynamic data function and static data function of the city to be estimated by combining the basic data characteristics corresponding to each basic urban data, and assign a corresponding analysis model layer to each basic urban data. Step 13: Input the basic data of each city into the preset multi-system coupling failure model, and perform functional analysis on the basic data of the city in each analysis model layer to obtain several dynamic coupling failure output results and several static coupling failure output results of the city to be estimated. Step 14: Based on the basic data of each city, deduce the industrial chain of the city to be estimated, and use the basic data characteristics corresponding to the basic data of each city to combine the dynamic coupling failure output result and the static coupling failure output result to obtain the interaction information between different industrial chains and generate an industrial association map.

[0024] In this example, data attributes represent the basic presentation attributes of the city's basic data; In this example, the basic data features represent the characteristics presented by the city's basic data; In this example, dynamic data class and static data class represent the status categories corresponding to the basic urban data; In this example, the dynamic data function represents the function of the dynamic data class in the city to be estimated, and the static data function represents the function of the static data class in the city to be estimated. In this example, the interactive information represents the information generated when different industry chains collaborate.

[0025] The working principle and beneficial effects of the above technical solution are as follows: First, by identifying data attributes and performing feature enhancement processing, the potential value of basic urban data can be effectively mined, data noise interference can be reduced, and the integrity and accuracy of basic data features can be improved, avoiding subsequent analysis biases caused by data quality issues. Then, based on data attributes, dynamic and static data classes are divided, and data functions are constructed and analysis model layers are allocated accordingly. This achieves precise matching between data and analysis models, satisfying both the need for real-time updates and analysis of dynamic data and the need for stable baseline analysis of static data, thus improving the targeting and efficiency of data processing. Furthermore, functional analysis of the data is performed in the hierarchical model, which can output dynamic and static coupling failure results separately, fully reflecting the multi-system coupling failure process. The dual impact of dynamic changes and static scenarios allows for a more comprehensive output of coupled failure results, avoiding the omission of key failure information in single-dimensional analysis. Finally, by combining the basic characteristics of the data to combine the two types of failure results, the industrial chain is deduced and an industrial correlation map is generated. This can accurately capture the interaction relationships between different industrial chains based on data characteristics. The industrial correlation map includes both the static basic correlation of the industrial chain and the dynamic correlation of coupled failure impact, providing more realistic map support for subsequent economic transmission path construction and loss analysis. This further enhances the scientificity and reliability of the entire assessment method. In this way, through refined data processing and hierarchical analysis, a precise and reliable foundation is laid for assessing the economic impact of multi-system coupled failures on the urban industrial chain, with significant beneficial effects.

[0026] Example 3

[0027] Based on Example 2, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains further includes: Based on the industry association map, construct and determine several related dynamic coupling failure output results and several related static coupling failure output results for each of the industry chains, and construct dynamic execution functions and static execution functions for each of the industry chains. The dynamic effectiveness of the dynamic execution function and the static effectiveness of the static execution function are analyzed based on the industrial execution process corresponding to each of the aforementioned industrial chains. Based on the dynamic functional effectiveness and the static functional effectiveness, several functional failure information corresponding to the industrial chain are derived, and a failure report for each industrial chain is generated and displayed.

[0028] In this example, dynamic execution functions represent the dynamic work performed in the supply chain, such as real-time production scheduling and logistics adaptation functions. In this example, static execution functions represent static tasks performed in the industry chain, such as ensuring basic production capacity and maintaining fixed cooperative relationships. In this example, the function failure information represents the information presented when the execution function in the supply chain fails; In this example, the dynamic function effectiveness represents the degree of effectiveness used to evaluate the dynamic execution functions of the supply chain, and the calculation formula is as follows: ; In this example, static function effectiveness represents the degree to which the static execution functions of the supply chain are evaluated, and the calculation formula is as follows: .

[0029] The working principle and beneficial effects of the above technical solution are as follows: First, based on the constructed industry association map, the dynamic and static coupling failure output results corresponding to each industry chain are clarified. Then, the dynamic and static execution functions of each industry chain are built in a targeted manner. Next, combined with the complete industry execution process of the industry chain from raw material procurement, production and processing to product sales, the dynamic and static functional effectiveness of the dynamic execution functions are analyzed respectively. Finally, based on the numerical changes of the two types of functional effectiveness, the specific functional failure information of the industry chain is derived, and an industry chain failure report containing the failure type, degree and affected links is generated. By achieving precise matching between the failure results and the industry chain through the industry association map, the function construction is more targeted, avoiding interference from irrelevant information. The functional effectiveness is evaluated from both dynamic and static dimensions, comprehensively covering the operation status of the industry chain, reducing the one-sidedness of single-dimensional evaluation. The visualized failure report can intuitively present the failure problems of the industry chain, providing managers with a clear basis for quickly formulating repair strategies and optimizing system coupling relationships, significantly improving the refinement and decision-making efficiency of urban industry chain risk management.

[0030] Example 4

[0031] Based on Example 1, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains, step 2 includes: Step 21: Determine several financial flow items corresponding to each of the industrial chains based on the industrial association map, and obtain the flow characteristics corresponding to each of the financial flow items. Obtain the real-time financial data of the city to be valued, and sample the real-time financial data according to the flow characteristics to obtain several financial data of each of the industrial chains. Step 22: Locate the associated financial data corresponding to each financial data in the industry association map, construct the capital flow process of each industry chain by combining the financial flow items corresponding to each financial data, identify the data value corresponding to each financial data, and construct the real-time capital flow characteristics corresponding to the industry chain based on the data value and the capital flow process. Step 23: Construct several capital chains in the industrial chain based on the real-time capital flow characteristics and capital flow process corresponding to each industrial chain, determine the capital interaction relationship between different industrial chains, and trace the capital chains by combining the capital flow direction corresponding to each financial flow item. Step 24: Based on the capital flow situation corresponding to each capital chain and the capital interaction relationship between different industrial chains, identify the economic expenditure and economic income corresponding to each industrial chain in the industrial association map, and generate the economic transmission path corresponding to each industrial chain.

[0032] In this example, financial current items represent items that involve expenditures or receipts of funds; In this example, the flow characteristics include expenditure characteristics and income characteristics; In this example, financial data refers to the data generated when funds are spent or received.

[0033] The working principle and beneficial effects of the above technical solution are as follows: First, by identifying the financial flow items corresponding to each industrial chain through an industrial correlation map, and sampling real-time financial data according to flow characteristics, it can accurately filter out financial data directly related to the industrial chain, avoid interference from irrelevant financial data, ensure the relevance of the data foundation, and lay an accurate data foundation for the subsequent construction of capital flow characteristics. Then, by combining related financial and financial flow items, the capital flow process is constructed, and real-time capital flow characteristics are formed based on data values. This can clearly capture the real-time flow status of funds in the industrial chain, truly reflect the current capital operation pattern of the industrial chain, make up for the insufficiency of static data in reflecting dynamic changes in funds, and further enhance the real-time capital flow characteristics and capital flow characteristics. The flow process constructs a capital chain, and by combining capital interaction relationships and flow direction for capital tracing, it can not only fully sort out the capital network within a single industrial chain, but also clarify the capital connections between industrial chains. Ultimately, by identifying economic income and expenditure, it generates economic transmission paths. These paths not only cover the economic transmission logic within the industrial chain, but also reflect the economic linkages between industrial chains. This provides a comprehensive and realistic path basis for subsequent analysis of economic losses at the point of link interruption and assessment of the impact of multi-system coupling failures on the industrial chain economy. It significantly improves the accuracy and practicality of economic impact assessment, provides precise, comprehensive, and realistic support for constructing urban industrial chain economic transmission paths, and significantly enhances the reliability and pertinence of subsequent economic impact assessments.

[0034] Example 5

[0035] Based on Example 1, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains, step 3 includes: Step 31: Divide each of the economic transmission paths into several path links, and construct the economic hash value corresponding to each path link in combination with the industry association map, construct the hash tree corresponding to each economic transmission link, and filter the target path links with interruption characteristics according to the data integrity features corresponding to each branch in the hash tree. Step 32: Analyze the link interruption points corresponding to each target path link in the economic transmission link based on the real-time capital flow characteristics of each industrial chain, and identify several interruption-related links corresponding to each link interruption point in the industrial association map. Step 33: Utilize the temporal neural network to perform structural relationship analysis on each link interruption point and the corresponding interruption-related link, construct an economic graph structure between the link interruption point and the corresponding interruption-related link, and capture the economic information corresponding to each interruption-related link in the economic graph structure based on the interruption economic value corresponding to the link interruption point. Step 34: Locate the target economic information with affected characteristics, and divide the target economic information into directly affected economic information and indirectly affected economic information according to the feature values ​​corresponding to the affected characteristics, and construct the direct / indirect economic losses caused by each link interruption point.

[0036] In this example, the path link represents an independent and complete economic execution process within the economic transmission path; In this example, the economic hash value represents the hash value of a path link; In this example, the interruption-related link refers to the link associated with the point of link interruption.

[0037] The working principle and beneficial effects of the above technical solution are as follows: By breaking down the economic transmission path into path links, and combining the industry association map to construct economic hash values ​​for each link and form a hash tree, the target path links can be screened by using the data integrity features of the hash tree branches. This can accurately locate links with interruption characteristics from the complex economic transmission links, effectively avoiding the omission of interruption nodes due to the length of the links, and laying an accurate foundation for subsequent link interruption point location. After locating the link interruption point, the interruption-related links corresponding to the interruption point are identified through the industry association map, breaking the analysis limitations of a single industrial chain or a single link, and fully capturing the radiation range of the interruption point on the surrounding related links. This ensures that the assessment of the impact of coupling failure extends to the entire related network. Furthermore, the structural relationship analysis of the interruption point and interruption-related links is carried out using a temporal neural network, constructing an economic graph structure and capturing the economic information of the interruption-related links. This can clearly present the dynamic economic association logic between the interruption point and each related link. Finally, by screening the target economic information and classifying it into directly affected economic information and indirectly affected economic information according to feature values, the direct and indirect economic losses are constructed, realizing the scientific breakdown and accurate quantification of loss types. This classification method avoids conflating losses of different natures and provides a clear basis for assessing the overall impact of multi-system coupling failures on the industrial chain economy. This makes the assessment results more consistent with actual economic scenarios and provides precise data support for cities to formulate industrial chain risk response strategies.

[0038] Example 6

[0039] Based on Example 1, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains, step 4 includes: Step 41: Input the direct / indirect economic losses into the preset multi-system coupling failure model, match the basic urban data and the direct / indirect economic losses in the preset multi-system coupling failure model, and determine several explicit impact characteristics of the city to be estimated; Step 42: Analyze the loss manifestation characteristics of each direct / indirect economic loss in the industrial correlation map in the preset multi-system coupling failure model, and identify the implicit impact characteristics of each loss manifestation characteristic on different economic transmission paths in the industrial correlation map; Step 43: Statistically analyze several explicit impact characteristics and corresponding explicit impact values ​​for each of the economic transmission paths, as well as several implicit impact characteristics and corresponding implicit impact values, to determine the economic loss value corresponding to each of the economic transmission paths. Step 44: Locate emergency economic transmission paths where the economic loss value exceeds the loss threshold, and, in conjunction with the emergency industrial chain corresponding to the emergency economic transmission path, determine the industrial scope corresponding to the emergency industrial chain and issue corresponding alarms.

[0040] In this example, explicit impact characteristics represent the economic impacts that have already occurred in the city to be estimated, while implicit impact characteristics represent the economic impacts that have not yet occurred in the city to be estimated. In this example, industry scope refers to the industrial coverage of an industry chain.

[0041] The working principle and beneficial effects of the above technical solution are as follows: To significantly improve the comprehensiveness, accuracy, and practicality of early warning of economic risks in urban industrial chains under multi-system coupling failures, the direct / indirect economic losses are first input into a preset model. Then, by matching basic urban data, explicit impact characteristics are determined, ensuring that loss analysis is deeply integrated with the actual industrial base and system configuration of the city to be assessed. Next, the loss manifestation characteristics are analyzed in the model, and its implicit impact characteristics on economic transmission paths are identified, fully covering the short-term direct impact and long-term implicit impact of coupling failures on the industrial chain. Furthermore, by statistically analyzing the explicit and implicit impact values ​​of economic transmission paths, the corresponding economic loss value is comprehensively determined, avoiding underestimation or overestimation of losses due to single-dimensional accounting. Finally, by identifying emergency economic transmission paths with loss values ​​exceeding thresholds, the corresponding emergency industrial chains are identified and their industrial scope is clarified. Targeted alarm work then allows urban management departments to quickly focus on high-risk industrial chains and critical paths, promptly allocate resources, and initiate emergency measures, minimizing the economic impact of coupling failures on the urban industrial chain.

[0042] Example 7

[0043] Based on Example 6, the method for assessing the economic impact of multi-system coupling failure on urban industrial chains further includes: When the total value of the explicit impact corresponding to several explicit impact features is greater than the loss threshold, it is determined that an emergency has occurred in the city to be estimated, the emergency impact range corresponding to the emergency is identified, and corresponding alarm work is carried out.

[0044] The working principle and beneficial effects of the above technical solution are as follows: when the affected value of the city to be evaluated reaches the threshold, it indicates that the city may be facing a huge economic event. Timely reminders can reduce economic losses.

[0045] Example 8

[0046] This embodiment provides a system for assessing the economic impact of multi-system coupling failures on urban industrial chains, such as... Figure 2 As shown, it includes: The functional analysis module is used to input the basic urban data of the city to be evaluated into a preset multi-system coupling failure model for functional analysis, and to construct an industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results. The economic analysis module is used to generate real-time capital flow characteristics for each of the industrial chains by using the industrial association map and the real-time financial data of the city to be valued, and to construct the economic transmission path for each of the industrial chains respectively. The loss analysis module is used to identify the link interruption points contained in the economic transmission path, predict the economic transmission path of the link interruption points using a time-series neural network, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. The early warning analysis module is used to input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and to issue an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

[0047] In this example, the basic city data represents the data generated by the various industrial chains in the city to be evaluated when they perform their work, as well as the city's construction data. In this example, the coupling failure output result represents the output result after functional analysis of the preset multi-system coupling failure model; In this example, the pre-defined multi-system coupling failure model represents a mathematical model used to analyze the joint failure of multiple subsystems or components in a complex system under interaction. In this example, real-time financial data represents financial-related, real-time updated data for the city to be evaluated; In this example, real-time capital flow characteristics represent the features exhibited when capital flows within the industrial chain; In this example, the economic transmission path represents the path formed by economic expenditures and economic incomes in the industrial chain; In this example, direct / indirect economic loss refers to the economic loss caused to the city under evaluation due to link disruption; In this example, the link interruption point represents the location in the economic transmission path where funding is interrupted; In this example, the loss threshold is set at 0.015% of the total economic value of the city to be estimated.

[0048] The working principle and beneficial effects of the above technical solution are as follows: To fill the gap in existing technology and ensure the stable operation of urban industrial chains, an assessment method that considers multi-system coupling failures, accurately identifies the transmission path of industrial chains, predicts economic losses in real time, and has a closed-loop early warning function is proposed. Based on the basic data of the city to be assessed, the system functions are analyzed by pre-setting a multi-system coupling failure model. Based on this, an industrial correlation map between different industrial chains is constructed. Then, real-time financial data is combined to generate real-time capital flow characteristics of each industrial chain and to build economic transmission paths. Subsequently, the link breakpoints in the paths are identified, and the transmission path of the breakpoints is predicted using a time-series neural network. Direct and indirect economic losses are analyzed in conjunction with the industrial correlation map. Finally, the loss data is fed back into the model to derive the total loss value of the path breakpoints. If the loss exceeds a specified threshold, an alarm is triggered in the city. This approach fully considers the chain effect of multi-system coupling failures, dynamically and accurately captures the economic transmission law and loss situation of the industrial chain, forming a complete analytical closed loop. It effectively solves the problems of traditional assessments, such as ignoring system coupling, analysis lag, and lack of early warning mechanisms. This provides scientific and timely support for urban industrial chain risk prevention and emergency decision-making, ensuring the stable operation of urban industrial chains.

[0049] Example 9

[0050] This embodiment provides a device for assessing the economic impact of multi-system coupling failures on urban industrial chains, such as... Figure 3 As shown, it includes: the evaluation system described in Example 8; It also includes a risk presentation system, which is used to construct and display visual risk information of the city to be assessed based on the economic loss value and the industry association map.

[0051] The working principle and beneficial effects of the above technical solution are as follows: By using visualization technology, the risk information of the city to be assessed is displayed to relevant personnel, making it easier for them to quickly obtain relevant information and make corresponding decisions.

[0052] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for assessing the economic impact of multi-system coupling failures on urban industrial chains, characterized in that, include: Step 1: Input the basic urban data of the city to be evaluated into the preset multi-system coupling failure model for functional analysis, and construct the industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results; Step 2: Using the industry association map and the real-time financial data of the city to be valued, generate real-time capital flow characteristics for each of the industrial chains, and construct the economic transmission path for each of the industrial chains respectively; Step 3: Identify the link interruption points contained in the economic transmission path, use a time-series neural network to predict the economic transmission path of the link interruption points, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. Step 4: Input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and trigger an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

2. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 1, characterized in that, Step 1 includes: Step 11: Obtain several basic data points of the city to be estimated, identify the data attributes corresponding to each basic data point of the city, and perform feature enhancement processing on each basic data point of the city to obtain the basic data features corresponding to each basic data point of the city. Step 12: Divide the basic urban data into dynamic data class and static data class according to the data attributes, construct the dynamic data function and static data function of the city to be estimated by combining the basic data characteristics corresponding to each basic urban data, and assign a corresponding analysis model layer to each basic urban data. Step 13: Input the basic data of each city into the preset multi-system coupling failure model, and perform functional analysis on the basic data of the city in each analysis model layer to obtain several dynamic coupling failure output results and several static coupling failure output results of the city to be estimated. Step 14: Based on the basic data of each city, deduce the industrial chain of the city to be estimated, and use the basic data characteristics corresponding to the basic data of each city to combine the dynamic coupling failure output result and the static coupling failure output result to obtain the interaction information between different industrial chains and generate an industrial association map.

3. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 2, characterized in that, Also includes: Based on the industry association map, construct and determine several related dynamic coupling failure output results and several related static coupling failure output results for each of the industry chains, and construct dynamic execution functions and static execution functions for each of the industry chains. The dynamic effectiveness of the dynamic execution function and the static effectiveness of the static execution function are analyzed based on the industrial execution process corresponding to each of the aforementioned industrial chains. Based on the dynamic functional effectiveness and the static functional effectiveness, several functional failure information corresponding to the industrial chain are derived, and a failure report for each industrial chain is generated and displayed.

4. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 1, characterized in that, Step 2 includes: Step 21: Determine several financial flow items corresponding to each of the industrial chains based on the industrial association map, and obtain the flow characteristics corresponding to each of the financial flow items. Obtain the real-time financial data of the city to be valued, and sample the real-time financial data according to the flow characteristics to obtain several financial data of each of the industrial chains. Step 22: Locate the associated financial data corresponding to each financial data in the industry association map, construct the capital flow process of each industry chain by combining the financial flow items corresponding to each financial data, identify the data value corresponding to each financial data, and construct the real-time capital flow characteristics corresponding to the industry chain based on the data value and the capital flow process. Step 23: Construct several capital chains in the industrial chain based on the real-time capital flow characteristics and capital flow process corresponding to each industrial chain, determine the capital interaction relationship between different industrial chains, and trace the capital chains by combining the capital flow direction corresponding to each financial flow item. Step 24: Based on the capital flow situation corresponding to each capital chain and the capital interaction relationship between different industrial chains, identify the economic expenditure and economic income corresponding to each industrial chain in the industrial association map, and generate the economic transmission path corresponding to each industrial chain.

5. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 1, characterized in that, Step 3 includes: Step 31: Divide each of the economic transmission paths into several path links, and construct the economic hash value corresponding to each path link in combination with the industry association map, construct the hash tree corresponding to each economic transmission link, and filter the target path links with interruption characteristics according to the data integrity features corresponding to each branch in the hash tree. Step 32: Analyze the link interruption points corresponding to each target path link in the economic transmission link based on the real-time capital flow characteristics of each industrial chain, and identify several interruption-related links corresponding to each link interruption point in the industrial association map. Step 33: Utilize the temporal neural network to perform structural relationship analysis on each link interruption point and the corresponding interruption-related link, construct an economic graph structure between the link interruption point and the corresponding interruption-related link, and capture the economic information corresponding to each interruption-related link in the economic graph structure based on the interruption economic value corresponding to the link interruption point. Step 34: Locate the target economic information with affected characteristics, and divide the target economic information into directly affected economic information and indirectly affected economic information according to the feature values ​​corresponding to the affected characteristics, and construct the direct / indirect economic losses caused by each link interruption point.

6. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 1, characterized in that, Step 4 includes: Step 41: Input the direct / indirect economic losses into the preset multi-system coupling failure model, match the basic urban data and the direct / indirect economic losses in the preset multi-system coupling failure model, and determine several explicit impact characteristics of the city to be estimated; Step 42: Analyze the loss manifestation characteristics of each direct / indirect economic loss in the industrial correlation map in the preset multi-system coupling failure model, and identify the implicit impact characteristics of each loss manifestation characteristic on different economic transmission paths in the industrial correlation map; Step 43: Statistically analyze several explicit impact characteristics and corresponding explicit impact values ​​for each of the economic transmission paths, as well as several implicit impact characteristics and corresponding implicit impact values, to determine the economic loss value corresponding to each of the economic transmission paths. Step 44: Locate emergency economic transmission paths where the economic loss value exceeds the loss threshold, and, in conjunction with the emergency industrial chain corresponding to the emergency economic transmission path, determine the industrial scope corresponding to the emergency industrial chain and issue corresponding alarms.

7. The method for assessing the economic impact of multi-system coupling failure on urban industrial chains as described in claim 6, characterized in that, Also includes: When the total value of the explicit impact corresponding to several explicit impact features is greater than the loss threshold, it is determined that an emergency has occurred in the city to be estimated, the emergency impact range corresponding to the emergency is identified, and corresponding alarm work is carried out.

8. A system for assessing the economic impact of multi-system coupling failures on urban industrial chains, characterized in that: include: The functional analysis module is used to input the basic urban data of the city to be evaluated into a preset multi-system coupling failure model for functional analysis, and to construct an industrial association map between different industrial chains in the city to be evaluated based on the coupling failure output results. The economic analysis module is used to generate real-time capital flow characteristics for each of the industrial chains by using the industrial association map and the real-time financial data of the city to be valued, and to construct the economic transmission path for each of the industrial chains respectively. The loss analysis module is used to identify the link interruption points contained in the economic transmission path, predict the economic transmission path of the link interruption points using a time-series neural network, and analyze the direct / indirect economic losses of the link interruption points in conjunction with the industry association map. The early warning analysis module is used to input the direct / indirect economic losses into the preset multi-system coupling failure model to derive the economic loss value caused by each path breakpoint, and to issue an alarm in the corresponding city to be estimated when the economic loss value exceeds the specified loss threshold.

9. An assessment device for the economic impact of multi-system coupling failure on urban industrial chains, characterized in that, include: The evaluation system as described in claim 8; It also includes a risk presentation system, which is used to construct and display visual risk information of the city to be estimated based on the economic loss value and the industry association map.

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