Rural regional system toughness evaluation method and system, terminal and storage medium

Abstract

The invention relates to the technical field of geographic information processing, and discloses a rural regional system toughness evaluation method and system, a terminal and a storage medium, and the method comprises the steps: obtaining region related data of a target region, constructing a plurality of different element networks, and carrying out the aggregation processing of all element networks, and obtaining a rural regional system network; performing evaluation processing on the resistance toughness of the rural regional system network to obtain a resistance toughness evaluation result, and performing evaluation processing on the change toughness of the rural regional system network to obtain a change toughness evaluation result; and setting a dynamic disturbance strategy, performing toughness evaluation on the rural regional system network to obtain a toughness loss result, and performing combined analysis on the resistance toughness evaluation result, the change toughness evaluation result and the toughness loss result to obtain a rural toughness evaluation result. According to the method, the toughness of the rural regional system is evaluated by establishing a toughness construction framework and a dynamic and static combined network toughness measurement method, and the accuracy of a toughness evaluation result is improved.

Description

Technical Field

[0001] The present invention relates to the field of geographic information processing technology, and in particular to a resilience assessment method, system, terminal and computer-readable storage medium for a rural regional system. Background Art

[0002] Currently, there are various methods for evaluating rural resilience (rural resilience refers to the ability of rural regional systems to maintain stability, reduce losses, and seek transformation and development through internal adjustments and external adaptation when responding to risk shocks such as natural disasters). However, due to significant differences in urban and rural attributes, traditional resilience indicator systems based on statistical data struggle to systematically describe the resilience loss mechanisms of rural regional systems due to issues such as inconsistent statistical calibers for data integration and varying factor attributes. Furthermore, as a geographical region encompassing multiple urban and rural entities, existing techniques for studying rural regional systems (formed by the interaction between urban and rural elements such as people, land, and production) fail to adequately consider the multiple human or multi-source interference within the urban-rural human-land coupled system, resulting in inaccurate resilience assessments of rural regional systems.

[0003] Therefore, the existing technology still needs to be improved and developed. Summary of the Invention

[0004] The main purpose of the present invention is to provide a resilience assessment method, system, terminal and storage medium for rural regional systems, aiming to solve the problem that the existing technology is difficult to systematically describe the resilience loss mechanism of rural regional systems, and does not fully consider the interference from multiple sources in the urban-rural human-land coupling system, resulting in inaccurate resilience assessment of rural regional systems.

[0005] To achieve the above objectives, the present invention provides a method for assessing the resilience of a rural regional system, comprising the following steps: Acquiring regional data of a target area, constructing a plurality of different element networks based on the regional data, and aggregating all the element networks to obtain a rural regional system network; Evaluating the resistance resilience of the rural regional system network according to the resistance resilience index to obtain a resistance resilience evaluation result, and evaluating the transformation resilience of the rural regional system network according to the transformation resilience index to obtain a transformation resilience evaluation result; Setting corresponding dynamic perturbation strategies according to the node elements, edge elements, and network elements of the rural regional system network, and performing resilience assessment on the rural regional system network according to the dynamic perturbation strategies to obtain resilience loss results; The resistance resilience assessment results, the change resilience assessment results and the resilience loss results are combined and analyzed to obtain the rural resilience assessment results.

[0006] Optionally, the rural regional system resilience assessment method, wherein obtaining regional-related data of a target area, constructing a plurality of different element networks based on the regional-related data, and aggregating all the element networks to obtain a rural regional system network, specifically includes: Acquiring area-related data of the target area, wherein the area-related data includes navigation data, traffic network data, and industry-related data; constructing networks based on the navigation data, the traffic network data, and the industry-related data to obtain a plurality of different element networks, wherein the element network is any one of a population flow network, a spatial connection network, and an industry circulation network; All the element networks are processed separately into urban and rural areas and the urban network is screened out to obtain a plurality of rural element networks, and all the rural element networks are aggregated to obtain a rural regional system network.

[0007] Optionally, in the resilience assessment method for rural regional systems, the resilience index includes a network clustering index, a network hierarchical index, and a network transmission index; The resilience assessment of the rural regional system network is performed according to the resilience index to obtain a resilience assessment result, specifically including: Calculating the clustering coefficient of each node in the rural area system network according to the network clustering index to obtain multiple local clustering coefficients, and calculating the average value of all the local clustering coefficients to obtain a network agglomeration index; quantifying the quality of the community structure in the rural regional system network according to the network hierarchical index to obtain a modularity value, and characterizing the modularity value to obtain a network hierarchical index; Calculating an average value of the shortest path lengths between all pairs of nodes in the rural area system according to the network transmission performance index to obtain an average path length, and obtaining a network transmission performance index according to the average path length; A resistance resilience evaluation result is obtained according to the network clustering index, the network hierarchical index and the network transmission index.

[0008] Optionally, in the resilience assessment method for a rural regional system, the clustering coefficient of each node in the rural regional system network is calculated according to the network clustering index, specifically as follows: ; The quantification of the quality of the community structure in the rural regional system network according to the network hierarchical index is specifically as follows: ; The average value of the shortest path lengths between all node pairs in the rural area system is calculated based on the network transmission index, specifically: ; in, For nodes The local clustering coefficient of For nodes The degree, is the number of interconnected edges that actually exist in the rural area system network, is the modular value, For nodes and nodes The actual connection between and Node and nodes The degree, is the total number of connections in the rural area system network, is the Kroneckerdelta function, and Node and nodes The community number to which it belongs, is the average path length of the rural area system network, is the total number of nodes in the rural area system network, For nodes and nodes The shortest path length between .

[0009] Optionally, in the resilience assessment method for rural regional systems, the transformation resilience index includes a dynamic network resilience index, a minimum graph resilience index, and a mean flow resilience index; The transformation resilience of the rural regional system network is evaluated based on the transformation resilience index to obtain the transformation resilience evaluation result, which specifically includes: Calculating a pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second average self-reorganization value, and comparing the second average self-reorganization value with the first average self-reorganization value to obtain a self-reorganization index; Calculating an initial flow ratio of the rural area system network according to the minimum graph resilience index to obtain a first flow ratio, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second flow ratio, and comparing the second flow ratio with the first flow ratio to obtain minimum graph flow information; performing weighted calculation on the shortest path lengths between all pairs of nodes in the rural area system network according to the average flow resilience index to obtain a weighted shortest path length, and obtaining an average flow value according to the weighted shortest path length; A resistance toughness evaluation result is obtained according to the self-reorganization index, the minimum graph flow information and the average flow value.

[0010] Optionally, the resilience assessment method for a rural area system, wherein the step of calculating a pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value, specifically includes: Acquiring all self-adjusting nodes of the rural regional system network according to the dynamic network resilience index, and calculating self-reorganization values of all the self-adjusting nodes to obtain a plurality of self-reorganization values; Calculating an average value of all the self-recombination values to obtain a first average self-recombination value; The self-reorganization values of all the self-adjusting nodes are calculated to obtain multiple self-reorganization values, specifically: ; in, is the self-recombination value, is the average node degree of the self-adjusting nodes.

[0011] Optionally, the resilience assessment method for a rural area system, wherein the step of calculating the initial traffic ratio of the rural area system network according to the minimum graph resilience index to obtain a first traffic ratio, specifically includes: Calculating the flow attribute of each edge in the rural regional system network according to the minimum graph resilience index to obtain multiple flow attributes, and summing all the flow attributes to obtain an initial total flow; Connected component search is performed on the path flows of all node pairs in the rural area system network to obtain a maximum flow subgraph, flow calculation is performed on the maximum flow subgraph to obtain sub-flow, and the sub-flow is compared with the initial total flow to obtain a first flow ratio.

[0012] Optionally, in the method for assessing resilience of a rural regional system, the resilience assessment system of the rural regional system includes: a network aggregation module for acquiring regional relevant data of a target area, constructing a plurality of different element networks based on the regional relevant data, and aggregating all the element networks to obtain a rural regional system network; a static resilience assessment module, configured to assess the resistance resilience of the rural regional system network based on the resistance resilience index to obtain a resistance resilience assessment result, and to assess the change resilience of the rural regional system network based on the change resilience index to obtain a change resilience assessment result; a dynamic resilience assessment module, configured to set corresponding dynamic perturbation strategies based on the node elements, edge elements, and network elements of the rural regional system network, and to perform resilience assessment on the rural regional system network based on the dynamic perturbation strategies to obtain resilience loss results; The result generation module is used to combine and analyze the resistance resilience assessment results, the change resilience assessment results and the resilience loss results to obtain the rural resilience assessment results.

[0013] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a resilience assessment program for a rural area system stored on the memory and runnable on the processor, and when the resilience assessment program for the rural area system is executed by the processor, the steps of the resilience assessment method for the rural area system as described above are implemented.

[0014] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a resilience assessment program for a rural area system, and when the resilience assessment program for a rural area system is executed by a processor, the steps of the resilience assessment method for a rural area system as described above are implemented.

[0015] In the present invention, regional data of the target area is obtained, and a plurality of different element networks are constructed based on the regional data. All the element networks are aggregated to obtain a rural regional system network. The resistance resilience of the rural regional system network is evaluated based on the resistance resilience index to obtain a resistance resilience evaluation result. The transformation resilience of the rural regional system network is evaluated based on the transformation resilience index to obtain a transformation resilience evaluation result. A corresponding dynamic perturbation strategy is set based on the node elements, edge elements, and network elements of the rural regional system network, and the resilience of the rural regional system network is evaluated based on the dynamic perturbation strategy to obtain a resilience loss result. The resistance resilience evaluation result, the transformation resilience evaluation result, and the resilience loss result are combined and analyzed to obtain a rural resilience evaluation result. The present invention evaluates the resilience of the rural regional system by building a resilience construction framework and a dynamic and static combined network resilience measurement method, thereby improving the accuracy of the resilience evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of a preferred embodiment of the method for assessing resilience of a rural regional system according to the present invention; Figure 2 It is a structural diagram of a preferred embodiment of the resilience assessment system for a rural area system of the present invention; Figure 3 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clear and distinct, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0019] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features specified as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0020] The resilience assessment method of the rural regional system described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the resilience assessment method of the rural regional system includes the following steps: Step S10: Acquire regional related data of the target area, construct a plurality of different element networks based on the regional related data, and aggregate all the element networks to obtain a rural area system network.

[0021] Specifically, in an embodiment of the present invention, in order to solve the problem that the existing technology is difficult to systematically describe the resilience loss mechanism of the rural regional system, and the multiple sources of interference in the urban-rural human-land coupling system are not fully considered, resulting in inaccurate resilience assessment of the rural regional system, the present invention solves the above problems by building a resilience construction framework and a dynamic and static combined network resilience measurement method. Specifically, the present invention is based on the urban-rural element division type of "people, land, and production", focusing on the three subsystems of industry, rural areas and farmers, and constructing corresponding rural regional system element flow networks (i.e., element networks). The corresponding construction process is to obtain regional relevant data of the target area (for example, City A), wherein the regional relevant data includes navigation data, traffic network data and industry-related data (for example, industry investment data), and network is performed respectively according to the navigation data, the traffic network data and the industry-related data. Construct and obtain multiple different element networks, wherein the element network is any one of the population flow network, the spatial connection network and the industrial circulation network, and the population flow network, the spatial connection network and the industrial circulation network are all undirected and authorized multi-layer networks; then, it is necessary to screen the rural network (i.e., the rural element network). Since the flow of elements within urban areas is too frequent, the "city-city" edge relationship has a greater impact on the interaction relationship between urban and rural elements in the rural regional system. Therefore, it is necessary to screen out the network within the urban layer in the urban-rural network. The geographic spatial vector data of the village-level administrative district used in the present invention comes from Tiandi Map, and the three types of "village", "town" and "city" in the study area are divided to ensure that each village-level administrative district has a unique type attribute, that is, all the element networks are subjected to urban and rural division processing and urban network screening processing to obtain multiple rural element networks.

[0022] Afterwards, it is necessary to aggregate all the aforementioned rural element networks to obtain a rural regional system network. After aggregation, the key element relationships of the rural regional system can be integrated in a unified multi-layer network framework, revealing the coupling and coordination mechanisms between the subsystems. Aggregation not only enhances the understanding of the overall structure and function of the system, but also improves the ability to identify key nodes and vulnerable links, which helps to evaluate the resilience of the rural regional system under external disturbances and provide more systematic and targeted support for rural governance and decision-making. The rural regional system network is a typical multi-layer network, consisting of urban and rural nodes, and edges representing the flow relationships of multiple elements of "people, land and property" between them. The present invention uses the rural regional system network to Its adjacency matrix can be expressed as: ; in, is the node set of the network, that is, the urban and rural regional units, such as villages, towns and other spatial entities, is the edge set of the first layer network, representing the population flow relationship between urban and rural areas, that is, the flow of "people" elements. It is the edge set of the second-layer network, representing the spatial connection between urban and rural areas, that is, the flow of "land" elements. It is the edge set of the third-layer network, representing the capital flow relationship between urban and rural areas, that is, the flow of "production" factors.

[0023] Step S20: Evaluate and process the resistance resilience of the rural regional system network according to the resistance resilience index to obtain a resistance resilience evaluation result; and evaluate and process the change resilience of the rural regional system network according to the change resilience index to obtain a change resilience evaluation result.

[0024] Specifically, after obtaining the rural regional system network, because the rural regional system network is a typical regional network that includes multi-regional cooperative relationships. Generally, in short-term resistance and long-term transformation evolution, the network uses its internal static structural characteristics (for example, redundant connections, multi-center distributed structure, etc.) to maintain the integrity of structure and function, as well as the overall dynamic self-organizing ability to continuously adapt to new environmental conditions, which is considered to be a manifestation of high resilience; while resilience is an endogenous property of a system, the resilience of complex systems has several characteristics: (1) the subsystems within the system have different tolerance thresholds; (2) the subsystems influence each other, and the system has a certain self-organizing ability; (3) the disturbance sources of the system are diverse and complex. In a complex system, the change of one element can affect or promote the change of another level, because the change is not a zero-sum game, but this also means that the change of the system is a continuous and gradual process, which is actually difficult to track or measure. The risk attribute characteristics and thresholds of changes in different subsystems are different, and the overall system may have a weak board effect when facing the same disturbance. In essence, the system is defined as a collection of elements in mutual relationship, the combined behavioral structure of different elements within the system, and the interaction between the system and the environment is described as function. Therefore, the resilience measurement of rural regional system networks in this paper can be decomposed into three dimensions: "element-structure-function" to fully describe the changes in system resilience. On this basis, the dual characteristics of "resistance" and "transformation" of rural multi-flow network resilience are coupled to construct an indicator matrix within the "element-structure-function" dimension.

[0025] Resilience refers to the ability of a system to learn, integrate experience and knowledge, adjust its response to changing external drivers and internal processes, and continue to develop within its current stable domain. Therefore, the present invention has established an "agglomeration-hierarchy-transmission" resilience indicator system, which aims to describe the element linkage capacity, structural robustness, and functional transmission capacity of the rural regional system network under a static state. Transformation resilience, on the other hand, emphasizes the conditions under which interference (or perturbation) can shift a system from one equilibrium to another. Therefore, the present invention has established a "minimum graph-average flow-dynamic network" transformational resilience indicator system, which aims to characterize the resilience of the rural regional system network under long-term disturbances from the perspectives of dynamic element adaptation, optimal structural tolerance, and flexible functional allocation.

[0026] For the resilience assessment of rural regional system networks, the resilience of the rural regional system networks is assessed and processed according to the resilience index to obtain the resilience assessment result, wherein the resilience index includes network clustering index, network hierarchical index and network transmission index; and the network clustering index corresponds to network agglomeration, which measures the degree of connection between nodes and their neighbors in the network. Specifically, network agglomeration is the average value of the clustering coefficient of each node in the network. The clustering coefficient of a node refers to the ratio of the actual number of edges in the neighbors of the node to the maximum number of edges that may exist (that is, when fully connected); for a certain node , its local clustering coefficient It can be defined as: ; in, For nodes The local clustering coefficient of For nodes degree, that is, the degree of the node The number of directly connected neighboring nodes, is the number of interconnected edges that actually exist in the rural regional system network; then, the average value of all the local clustering coefficients is calculated to obtain the overall clustering coefficient (i.e., the network agglomeration index), and the corresponding expression is: ; in, is the network agglomeration index of the rural regional system network, is the node set of the rural area system network, is the total number of nodes in the rural area system network.

[0027] The network hierarchy index corresponds to network hierarchy, which is characterized by network modularity. Modularity is an indicator used to quantify the quality of the community structure in the network. Community structure refers to the property that network nodes are divided into multiple clusters, where nodes within a cluster are closely connected to each other, while nodes between clusters are less connected. The quality of the community structure in the rural regional system network is quantified based on the network hierarchy index to obtain a modularity value, and the corresponding expression is: ; in, is the modular value, For nodes and nodes The actual connection between and Node and nodes The degree, is the total number of connections in the rural area system network, is the Kronecker delta function (Kronecker function), and Node and nodes The community number to which it belongs, used to determine the node and nodes Are they from the same community? When , the result is 1, indicating that the two nodes are in the same community. When , the result is 0, indicating that the two nodes are not in the same community; thereafter, the modularity value is characterized to obtain the network hierarchical index.

[0028] The network transmission index corresponds to network transmission. As an indicator of connection efficiency, the network transmission line is represented by a simplified model of 1 divided by the average network path length. The average network path length represents the average of the shortest path lengths between all possible node pairs in the network. Therefore, a larger average path length often means that more hops may be required to reach between two nodes. A larger transmission performance means that the network has efficient information transmission function. A network with high transmission performance is easier to adjust dynamically because the failure of any node or link has little impact on the entire network. The network can quickly find an alternative path to continue functioning. Specifically, the average of the shortest path lengths between all node pairs in the rural area system is calculated based on the network transmission index to obtain the average path length. The corresponding expression is: ; in, is the average path length of the rural area system network, is the total number of nodes in the rural area system network, For nodes and nodes The shortest path length between them; then, the network transmission index is obtained according to the average path length, and the corresponding expression is: ; in, is the network transmission index; and then, the resistance resilience evaluation result is obtained according to the network agglomeration index, the network hierarchy index and the network transmission index.

[0029] To assess the transformational resilience of rural regional system networks, under a cyberattack scenario, when a network performance indicator collapses to 50% of its original state, the required cyberattack ratio is used as the resilience indicator for that performance indicator. This means that the transformational resilience of the rural regional system network is assessed based on the transformational resilience indicators, resulting in a transformational resilience assessment result. These transformational resilience indicators include the dynamic network resilience indicator, the minimum graph resilience indicator, and the average flow resilience indicator. The dynamic network resilience indicator aims to study how a network maintains functionality through adaptive reorganization of elements after the removal of key nodes or edges, taking into account network dynamics. Network dynamics can reflect the evolution of participating elements in real-world networks in response to crises (for example, changes in rural economic and social systems under the impact of urban financial crises). In networks with high dynamic network resilience indicators, elements can rapidly respond and dynamically adjust to persistent external disturbances through self-adjustment and overall optimization. Current resilience functions have evolved from low-dimensional models with limited node interactions and poor dynamics to high-dimensional complex networks with identifiable state parameters. The corresponding expression is: ; in, is the self-recombination value, and is a nonlinear function that follows the laws of dynamics. All nodes and adjacent nodes The interaction of For nodes The self-action, For nodes The self-action, and These two terms reflect the self-action of network nodes and the interaction between nodes, respectively. In this paper, the resilience of a system is measured by using an ordinary differential equation derived from a modified dynamic model (e.g., the Lotka-Volterra model) as a resilience dynamics model. The corresponding expression is: ; After that, we introduce the parameters and parameters , combining the dynamic model and the structural parameters. Since the network constructed by the present invention is an undirected weighted network, the parameters and parameters are 1 and the average node degree respectively , the expression obtained after substitution is: ; in, is the self-recombination value, is the average node degree of the self-adjusting nodes; then, all the self-adjusting nodes of the rural area system network are obtained according to the dynamic network resilience index, and the self-reorganization values of all the self-adjusting nodes are calculated to obtain multiple self-reorganization values; the average value of all the self-reorganization values is calculated to obtain a first average self-reorganization value; similarly, the post-disturbance self-reorganization value of the rural area system network is calculated to obtain a second average self-reorganization value; and the second average self-reorganization value is compared with the first average self-reorganization value to obtain a self-reorganization index, the corresponding expression of which is: ; in, (Dynamic Network Robustness) is the self-reorganization index, is the average self-reorganization value of the rural regional system network before the disturbance (i.e., the first average self-reorganization value), which reflects the self-regulation ability of each node in the rural regional system under normal conditions. It is the average self-reorganization value of the network after a disturbance (for example, attack or deletion of key nodes) (i.e., the second average self-reorganization value), indicating the level of recovery ability of the rural regional system after damage.

[0030] The minimum graph resilience index focuses on the structural stability under the extreme state of the network (for example, the minimum necessary connection), is closely related to the specific state of a single graph, emphasizes the performance of the network in a specific maximum subgraph, and pays more attention to the minimum performance of the network in the worst scenario. Specifically, the minimum graph resilience index measures the ratio of the maximum connected subgraph traffic in the network to the overall network traffic. If a higher proportion is removed, the minimum graph resilience index does not change, which means that the overall structure of the network is strong and can withstand more failures or interference and remain connected; if a smaller proportion is removed, it can significantly affect the connectivity of the network, indicating that the network may have potential vulnerabilities. This information is crucial for overall planning and improving network resilience. For rural regional system networks, each edge Each has a flow attribute , sum up all the traffic attributes and get the initial total traffic ; Use graph theory algorithms (e.g., depth-first search or breadth-first search) to search for connected components of the path flows of all node pairs in the rural area system network to obtain the maximum flow subgraph , for the maximum flow subgraph Perform flow calculation to obtain sub-flow , and the sub-flow is compared with the initial total flow to obtain a first flow ratio (i.e. the initial traffic ratio of the rural area system network), the corresponding expression is: ; Similarly, the attacked rural area system network (using The total flow rate Defined as: ; in, is the edge set of the rural area system network after the attack, and the self-reorganization value after the disturbance of the rural area system network is calculated to obtain the second traffic ratio (i.e., the traffic ratio of the rural area system network after the attack); then, the second traffic ratio is compared with the first traffic ratio to obtain the minimum graph traffic information, and the minimum graph traffic information is used. The corresponding expression is: .

[0031] The average flow resilience index focuses on the overall traffic distribution capability and stability of the network under normal operating conditions. It mainly reflects the performance of the network under random load and fault conditions, and focuses on the overall efficiency and traffic distribution of the network under general conditions. The average flow resilience index adds the calculation of edge weights to the commonly used network efficiency formula, and measures the overall load and traffic management capabilities of the network by calculating the average traffic between each pair of nodes; the shortest path length between all node pairs in the rural area system is weighted to obtain the weighted shortest path length, and the average flow value is obtained based on the weighted shortest path length. , the corresponding expression is: ; in, is the total number of nodes in the rural area system network, Nodes calculated using edge weights and nodes The weighted shortest path length between; and the weighted shortest path length is usually calculated by considering the weight as the distance or "cost", that is, the larger the weight, the greater the "distance" of the path, or the higher the "cost" of information passing through the edge.

[0032] Afterwards, a resistance toughness evaluation result is obtained according to the self-reorganization index, the minimum graph flow information and the average flow value.

[0033] Step S30: setting corresponding dynamic disturbance strategies according to the node elements, edge elements and network elements of the rural area system network, and performing resilience assessment on the rural area system network according to the dynamic disturbance strategies to obtain resilience loss results.

[0034] Specifically, in this embodiment of the present invention, the nodes, edges, and network elements of the constructed rural regional system network are used as perturbations. Through a selected perturbation strategy, a crisis scenario for the rural regional system is simulated, revealing the weak links in the current urban-rural integration. Because traditional resilience detection is often based on scale (i.e., static) locational space, it is necessary to shift this focus to relationship-based flow space, focusing on the spatial connectivity and element mobility between people, land, and property. Therefore, this invention introduces a "pressure-process-response" network resilience measurement method to quantify the resilience of rural regional systems under various shocks, and uses 50% of the original resilience index as the transformation resilience threshold. First, it is necessary to simulate risk disturbance scenarios by setting corresponding dynamic disturbance strategies based on the node elements, edge elements and network elements of the rural regional system network. For example, the various dynamic disturbance strategies proposed in the present invention include node-level dynamic disturbance strategies that directly affect the main functions of the rural area, such as the abandonment of transportation stations and the migration of market entities, as well as edge-level dynamic disturbance strategies that weaken the interaction between urban and rural elements, such as reduced population mobility and interrupted capital flow, and network-level dynamic disturbance strategies that threaten the overall stability of the system, such as economic crises and regional industrial reconstruction. Finally, the resilience of the rural regional system network is evaluated according to the dynamic disturbance strategies to obtain the resilience loss results.

[0035] Step S40: Combine and analyze the resistance resilience assessment result, the change resilience assessment result, and the resilience loss result to obtain a rural resilience assessment result.

[0036] Specifically, in an embodiment of the present invention, after obtaining the resistance resilience assessment results, the change resilience assessment results, and the resilience loss results, the resistance resilience assessment results, the change resilience assessment results, and the resilience loss results are combined and analyzed to obtain the rural resilience assessment results. The present invention constructs a resilience analysis framework for the rural regional system to perform network modeling and resilience assessment on the rural regional system. Because the rural regional system is formed by the interaction between urban and rural elements such as people, land, and production, and the flow of elements serves as the basis and goal of urban-rural integration and rural development, the present invention starts from the perspective of urban-rural relations, based on the resilience state and crisis response of multiple geographical flows, and introduces a multi-source risk attack disturbance scenario design to simulate the resilience loss of the internal subsystems and the entire system of the rural regional system. Through static states and dynamic changes, the resilience shortcomings of the rural regional system are identified, and a resilience improvement strategy for the rural regional system is proposed.

[0037] Furthermore, if Figure 2 As shown, based on the above-mentioned resilience assessment method for a rural regional system, the present invention also provides a resilience assessment system for a rural regional system, wherein the resilience assessment system for a rural regional system includes: The network aggregation module 51 is used to obtain regional related data of the target area, construct a plurality of different element networks based on the regional related data, and aggregate all the element networks to obtain a rural regional system network; a static resilience assessment module 52 for assessing the resilience of the rural regional system network based on the resilience index to obtain a resilience assessment result, and for assessing the transformation resilience of the rural regional system network based on the transformation resilience index to obtain a transformation resilience assessment result; A dynamic resilience assessment module 53 is configured to set corresponding dynamic perturbation strategies based on the node elements, edge elements, and network elements of the rural regional system network, and to perform resilience assessment on the rural regional system network based on the dynamic perturbation strategies to obtain a resilience loss result; The result generating module 54 is used to combine and analyze the resistance resilience assessment result, the change resilience assessment result and the resilience loss result to obtain a rural resilience assessment result.

[0038] Furthermore, if Figure 3 As shown, based on the above-mentioned resilience assessment method of the rural area system, the present invention also provides a terminal, which includes a processor 10, a memory 20 and a display 30. Figure 3 Only some of the components of the terminal are shown, but it should be understood that implementation of all of the shown components is not required, and more or fewer components may be implemented instead.

[0039] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Furthermore, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a resilience assessment program 40 for a rural area system is stored on the memory 20, and the resilience assessment program 40 for a rural area system can be executed by the processor 10, thereby realizing the resilience assessment method for a rural area system in the present application.

[0040] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 20, such as executing the resilience assessment method for the rural area system.

[0041] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch screen, etc. The display 30 is used to display information on the terminal and to display a visual user interface.

[0042] In one embodiment, when the processor 10 executes the program 40 for assessing resilience of a rural area system in the memory 20 , the following steps are implemented: Acquiring regional data of a target area, constructing a plurality of different element networks based on the regional data, and aggregating all the element networks to obtain a rural regional system network; Evaluating the resistance resilience of the rural regional system network according to the resistance resilience index to obtain a resistance resilience evaluation result, and evaluating the transformation resilience of the rural regional system network according to the transformation resilience index to obtain a transformation resilience evaluation result; Setting corresponding dynamic perturbation strategies according to the node elements, edge elements, and network elements of the rural regional system network, and performing resilience assessment on the rural regional system network according to the dynamic perturbation strategies to obtain resilience loss results; The resistance resilience assessment results, the change resilience assessment results and the resilience loss results are combined and analyzed to obtain the rural resilience assessment results.

[0043] The step of obtaining the region-related data of the target region, constructing a plurality of different element networks based on the region-related data, and aggregating all the element networks to obtain a rural regional system network specifically includes: Acquiring area-related data of the target area, wherein the area-related data includes navigation data, traffic network data, and industry-related data; constructing networks based on the navigation data, the traffic network data, and the industry-related data to obtain a plurality of different element networks, wherein the element network is any one of a population flow network, a spatial connection network, and an industry circulation network; All the element networks are processed separately into urban and rural areas and the urban network is screened out to obtain a plurality of rural element networks, and all the rural element networks are aggregated to obtain a rural regional system network.

[0044] The resilience index includes network clustering index, network hierarchy index and network transmission index; The resilience assessment of the rural regional system network is performed according to the resilience index to obtain a resilience assessment result, specifically including: Calculating the clustering coefficient of each node in the rural area system network according to the network clustering index to obtain multiple local clustering coefficients, and calculating the average value of all the local clustering coefficients to obtain a network agglomeration index; quantifying the quality of the community structure in the rural regional system network according to the network hierarchical index to obtain a modularity value, and characterizing the modularity value to obtain a network hierarchical index; Calculating an average value of the shortest path lengths between all pairs of nodes in the rural area system according to the network transmission performance index to obtain an average path length, and obtaining a network transmission performance index according to the average path length; A resistance resilience evaluation result is obtained according to the network clustering index, the network hierarchical index and the network transmission index.

[0045] The clustering coefficient of each node in the rural area system network is calculated according to the network clustering index, specifically: ; The quantification of the quality of the community structure in the rural regional system network according to the network hierarchical index is specifically as follows: ; The average value of the shortest path lengths between all node pairs in the rural area system is calculated based on the network transmission index, specifically: ; in, For nodes The local clustering coefficient of For nodes The degree, is the number of interconnected edges that actually exist in the rural area system network, is the modular value, For nodes and nodes The actual connection between and Node and nodes The degree, is the total number of connections in the rural area system network, is the Kroneckerdelta function, and Node and nodes The community number to which it belongs, is the average path length of the rural area system network, is the total number of nodes in the rural area system network, For nodes and nodes The shortest path length between .

[0046] The transformation resilience indicators include the dynamic network resilience index, the minimum graph resilience index and the average flow resilience index; The transformation resilience of the rural regional system network is evaluated based on the transformation resilience index to obtain the transformation resilience evaluation result, which specifically includes: Calculating a pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second average self-reorganization value, and comparing the second average self-reorganization value with the first average self-reorganization value to obtain a self-reorganization index; Calculating an initial flow ratio of the rural area system network according to the minimum graph resilience index to obtain a first flow ratio, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second flow ratio, and comparing the second flow ratio with the first flow ratio to obtain minimum graph flow information; performing weighted calculation on the shortest path lengths between all pairs of nodes in the rural area system network according to the average flow resilience index to obtain a weighted shortest path length, and obtaining an average flow value according to the weighted shortest path length; A resistance toughness evaluation result is obtained according to the self-reorganization index, the minimum graph flow information and the average flow value.

[0047] The step of calculating the pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value specifically includes: Acquiring all self-adjusting nodes of the rural regional system network according to the dynamic network resilience index, and calculating self-reorganization values of all the self-adjusting nodes to obtain a plurality of self-reorganization values; Calculating an average value of all the self-recombination values to obtain a first average self-recombination value; The self-reorganization values of all the self-adjusting nodes are calculated to obtain multiple self-reorganization values, specifically: ; in, is the self-recombination value, is the average node degree of the self-adjusting nodes.

[0048] The step of calculating the initial flow ratio of the rural area system network according to the minimum graph resilience index to obtain the first flow ratio specifically includes: Calculating the flow attribute of each edge in the rural regional system network according to the minimum graph resilience index to obtain multiple flow attributes, and summing all the flow attributes to obtain an initial total flow; Connected component search is performed on the path flows of all node pairs in the rural area system network to obtain a maximum flow subgraph, flow calculation is performed on the maximum flow subgraph to obtain sub-flow, and the sub-flow is compared with the initial total flow to obtain a first flow ratio.

[0049] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a resilience assessment program for a rural area system, and when the resilience assessment program for a rural area system is executed by a processor, the steps of the resilience assessment method for a rural area system as described above are implemented.

[0050] In summary, the present invention provides a resilience assessment method, system, terminal and storage medium for a rural regional system, the method comprising: obtaining regional relevant data of a target area, constructing a plurality of different element networks based on the regional relevant data, and aggregating all the element networks to obtain a rural regional system network; evaluating the resistance resilience of the rural regional system network according to the resistance resilience index to obtain a resistance resilience assessment result, and evaluating the change resilience of the rural regional system network according to the change resilience index to obtain a change resilience assessment result; setting corresponding dynamic perturbation strategies according to the node elements, edge elements and network elements of the rural regional system network, and evaluating the resilience of the rural regional system network according to the dynamic perturbation strategy to obtain a resilience loss result; combining and analyzing the resistance resilience assessment result, the change resilience assessment result and the resilience loss result to obtain a rural resilience assessment result. The present invention evaluates the resilience of the rural regional system by building a resilience construction framework and a dynamic and static combined network resilience measurement method, thereby improving the accuracy of the resilience assessment results.

[0051] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0052] Of course, those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware (such as a processor, controller, etc.) through a computer program. The program can be stored in a computer-readable storage medium that can be read by a computer. When executed, the program can include the processes in the above-described method embodiments. The computer-readable storage medium can be a memory, a magnetic disk, an optical disk, etc.

[0053] It should be understood that the application of the present invention is not limited to the above examples. For those skilled in the art, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for assessing the resilience of a rural regional system, characterized by: The resilience assessment method for rural regional systems includes: Acquiring regional data of a target area, constructing a plurality of different element networks based on the regional data, and aggregating all the element networks to obtain a rural regional system network; Evaluating the resistance resilience of the rural regional system network according to the resistance resilience index to obtain a resistance resilience evaluation result, and evaluating the transformation resilience of the rural regional system network according to the transformation resilience index to obtain a transformation resilience evaluation result; Setting corresponding dynamic perturbation strategies according to the node elements, edge elements, and network elements of the rural regional system network, and performing resilience assessment on the rural regional system network according to the dynamic perturbation strategies to obtain resilience loss results; The resistance resilience assessment results, the change resilience assessment results and the resilience loss results are combined and analyzed to obtain the rural resilience assessment results.

2. The resilience assessment method for rural regional systems according to claim 1, characterized in that: The step of obtaining the region-related data of the target region, constructing a plurality of different element networks based on the region-related data, and aggregating all the element networks to obtain a rural regional system network specifically includes: Acquiring area-related data of the target area, wherein the area-related data includes navigation data, traffic network data, and industry-related data; constructing networks based on the navigation data, the traffic network data, and the industry-related data to obtain a plurality of different element networks, wherein the element network is any one of a population flow network, a spatial connection network, and an industry circulation network; All the element networks are processed separately into urban and rural areas and the urban network is screened out to obtain a plurality of rural element networks, and all the rural element networks are aggregated to obtain a rural regional system network.

3. The resilience assessment method for rural regional systems according to claim 1, characterized in that: The resistance resilience index includes network clustering index, network hierarchy index and network transmission index; The resilience assessment of the rural regional system network is performed according to the resilience index to obtain a resilience assessment result, specifically including: Calculating the clustering coefficient of each node in the rural area system network according to the network clustering index to obtain multiple local clustering coefficients, and calculating the average value of all the local clustering coefficients to obtain a network agglomeration index; quantifying the quality of the community structure in the rural regional system network according to the network hierarchical index to obtain a modularity value, and characterizing the modularity value to obtain a network hierarchical index; Calculating an average value of the shortest path lengths between all pairs of nodes in the rural area system according to the network transmission performance index to obtain an average path length, and obtaining a network transmission performance index according to the average path length; A resistance resilience evaluation result is obtained according to the network clustering index, the network hierarchical index and the network transmission index.

4. The resilience assessment method for rural regional systems according to claim 3, characterized in that: The clustering coefficient of each node in the rural area system network is calculated according to the network clustering index, specifically: ； The quantification of the quality of the community structure in the rural regional system network according to the network hierarchical index is specifically as follows: ； The average value of the shortest path lengths between all node pairs in the rural area system is calculated based on the network transmission index, specifically: ； in, For nodes The local clustering coefficient of For nodes The degree, is the number of interconnected edges that actually exist in the rural area system network, is the modular value, For nodes and nodes The actual connection between and Node and nodes The degree, is the total number of connections in the rural area system network, is the Kronecker delta function, and Node and nodes The community number to which it belongs, is the average path length of the rural area system network, is the total number of nodes in the rural area system network, For nodes and nodes The shortest path length between .

5. The resilience assessment method for rural regional systems according to claim 1, characterized in that: The transformation resilience indicators include a dynamic network resilience indicator, a minimum graph resilience indicator, and a mean flow resilience indicator; The transformation resilience of the rural regional system network is evaluated based on the transformation resilience index to obtain the transformation resilience evaluation result, which specifically includes: Calculating a pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second average self-reorganization value, and comparing the second average self-reorganization value with the first average self-reorganization value to obtain a self-reorganization index; Calculating an initial flow ratio of the rural area system network according to the minimum graph resilience index to obtain a first flow ratio, calculating a post-disturbance self-reorganization value of the rural area system network to obtain a second flow ratio, and comparing the second flow ratio with the first flow ratio to obtain minimum graph flow information; performing weighted calculation on the shortest path lengths between all pairs of nodes in the rural area system network according to the average flow resilience index to obtain a weighted shortest path length, and obtaining an average flow value according to the weighted shortest path length; A resistance toughness evaluation result is obtained according to the self-reorganization index, the minimum graph flow information and the average flow value.

6. The resilience assessment method for rural regional systems according to claim 5, characterized in that: The calculating of the pre-disturbance self-reorganization value of the rural area system network according to the dynamic network resilience index to obtain a first average self-reorganization value specifically includes: Acquiring all self-adjusting nodes of the rural regional system network according to the dynamic network resilience index, and calculating self-reorganization values of all the self-adjusting nodes to obtain a plurality of self-reorganization values; Calculating an average value of all the self-recombination values to obtain a first average self-recombination value; The self-reorganization values of all the self-adjusting nodes are calculated to obtain multiple self-reorganization values, specifically: ； in, is the self-recombination value, is the average node degree of the self-adjusting nodes.

7. The resilience assessment method for rural regional systems according to claim 5, characterized in that: Calculating the initial flow ratio of the rural area system network according to the minimum graph resilience index to obtain a first flow ratio specifically includes: Calculating the flow attribute of each edge in the rural regional system network according to the minimum graph resilience index to obtain multiple flow attributes, and summing all the flow attributes to obtain an initial total flow; Connected component search is performed on the path flows of all node pairs in the rural area system network to obtain a maximum flow subgraph, flow calculation is performed on the maximum flow subgraph to obtain sub-flow, and the sub-flow is compared with the initial total flow to obtain a first flow ratio.

8. A resilience assessment system for rural regional systems, characterized by: The resilience assessment system of the rural regional system includes: a network aggregation module for acquiring regional relevant data of a target area, constructing a plurality of different element networks based on the regional relevant data, and aggregating all the element networks to obtain a rural regional system network; a static resilience assessment module, configured to assess the resistance resilience of the rural regional system network based on the resistance resilience index to obtain a resistance resilience assessment result, and to assess the change resilience of the rural regional system network based on the change resilience index to obtain a change resilience assessment result; a dynamic resilience assessment module, configured to set corresponding dynamic perturbation strategies based on the node elements, edge elements, and network elements of the rural regional system network, and to perform resilience assessment on the rural regional system network based on the dynamic perturbation strategies to obtain resilience loss results; The result generation module is used to combine and analyze the resistance resilience assessment results, the change resilience assessment results and the resilience loss results to obtain the rural resilience assessment results.

9. A terminal, characterized in that: The terminal includes a memory, a processor, and a program stored in the memory and executable on the processor. When the program is executed by the processor, the steps of the rural area system resilience assessment method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and the computer-readable storage medium stores a resilience assessment program for a rural area system. When the resilience assessment program for a rural area system is executed by a processor, the steps of the resilience assessment method for a rural area system as described in any one of claims 1-7 are implemented.

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