A method and system for site selection and screening of public infrastructure for both normal and emergency use.

Abstract

The application belongs to the technical field of urban planning, and discloses a flat and urgent dual-purpose public infrastructure site selection method and system. By constructing a graph structure of urban infrastructure, the dependence of candidate addresses on key upstream infrastructure is analyzed in depth, the individual vulnerability is quantified, and the common dependence risk of the site selection combination scheme is further evaluated, forming a closed-loop and systematic site selection screening process. It is just because of this interlocking and progressive analysis method that the application can effectively capture and quantify the "chain effect" caused by infrastructure failure, so as to screen out a flat and urgent dual-purpose public infrastructure site selection scheme with higher resilience in actual emergencies, and significantly improve the ability of the city to cope with emergencies.

Description

Technical Field

[0001] This application relates to the field of urban planning technology, and more specifically, to a method and system for site selection and screening of public infrastructure that can be used for both emergency and routine purposes. Background Technology

[0002] In urban planning and management, to enhance a city's ability to respond to emergencies, dual-purpose public infrastructure is typically planned and constructed, balancing daily use with emergency functions. These facilities serve as public service venues during normal times and can be quickly converted into emergency shelters, supply depots, or temporary medical points in emergencies. Existing site selection methods for dual-purpose public infrastructure usually involve collecting basic information such as population distribution, road network layout, and natural disaster risk areas within the target region. Based on this information, multiple candidate sites are scored to select the location that theoretically maximizes the community's emergency response capabilities.

[0003] However, this site selection method has a fundamental flaw. It treats various urban infrastructures, such as water supply, power supply, and transportation networks, as a stable and unchanging background, considering only their service capacity under ideal conditions. This method fails to fully account for the inherent vulnerabilities of these infrastructure systems and the close functional dependencies between them. A local failure in one infrastructure system can potentially trigger a chain reaction, completely altering the emergency response landscape of a region. For example, a water pipeline failure not only directly affects water supply services but may also disrupt traffic flow due to repair work, and even indirectly affect power supply, further weakening the region's overall emergency response capability. The existing site selection method cannot effectively capture and quantify this "chain reaction" caused by infrastructure failures, resulting in selected dual-use public infrastructure site selection schemes that may exhibit low resilience in actual emergencies and be unable to effectively cope with the complex and ever-changing risks of infrastructure failure. Therefore, scoring a location solely based on static geographical and demographic information is insufficient.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for selecting sites for public infrastructure that can be used for both normal and emergency purposes. This aims to solve the problem that existing site selection methods fail to fully consider the vulnerability of urban infrastructure and its functional dependencies, resulting in insufficient resilience of site selection schemes in the face of the risk of failure of complex infrastructure.

[0006] Firstly, this application provides a site selection method for dual-use public infrastructure, used to select sites for constructing dual-use public infrastructure from multiple candidate sites, including the following steps:

[0007] A1. Obtain the connection relationships and functional dependencies of various infrastructures and candidate addresses in the city, and generate a graph structure; each node in the graph structure represents an infrastructure or candidate address, and each edge represents the physical connection or functional dependency between the nodes.

[0008] A2. For each candidate address, based on the graph structure, identify the critical upstream infrastructure that the candidate address depends on;

[0009] A3. For each candidate address, determine the impact of the individual failure of each of the corresponding critical upstream infrastructures on the service capability of the candidate address, quantify the corresponding single vulnerability score, and use it to calculate the comprehensive vulnerability score of the candidate address;

[0010] A4. Based on the preset demand for dual-use facilities, select different combinations of the candidate addresses to form multiple site selection schemes;

[0011] A5. For each of the aforementioned location combination schemes, based on the graph structure, the critical upstream infrastructure, and the comprehensive vulnerability score, analyze the common dependency information of candidate addresses within the location combination scheme on the critical upstream infrastructure, in order to calculate the combined risk concentration of the location combination scheme; the common dependency information represents the association relationship between the critical upstream infrastructure commonly depended on by the candidate addresses within the location combination scheme and the corresponding candidate address;

[0012] A6. Select the site selection combination scheme with the lowest risk concentration as the site selection result for public infrastructure that can be used for both normal and emergency purposes.

[0013] Secondly, this application provides a site selection screening system for dual-use public infrastructure, used to screen the final site selection for dual-use public infrastructure from multiple candidate sites. The system includes:

[0014] The graph structure generation module is used to obtain the connection relationships and functional dependencies of various infrastructures and candidate addresses in the city, and generate a graph structure; each node in the graph structure represents an infrastructure or candidate address, and each edge represents the physical connection or functional dependency between the nodes.

[0015] A critical upstream infrastructure identification module is used to identify the critical upstream infrastructure on which each candidate address depends, based on the graph structure.

[0016] The vulnerability assessment module is used to determine the impact of the individual failure of each of the critical upstream infrastructures on the service capability of the candidate address for each candidate address, quantify the corresponding single vulnerability score, and use it to calculate the comprehensive vulnerability score of the candidate address.

[0017] The site selection combination scheme acquisition module is used to select different combinations of the candidate addresses to form multiple site selection combination schemes based on the preset quantity requirements of dual-use facilities.

[0018] The combined risk assessment module is used to analyze the common dependence information of candidate addresses within the location combination scheme on the critical upstream infrastructure based on the graph structure, the critical upstream infrastructure, and the comprehensive vulnerability score for each location combination scheme, in order to calculate the combined risk concentration of the location combination scheme; the common dependence information represents the association relationship between the critical upstream infrastructure commonly depended on by the candidate addresses within the location combination scheme and the corresponding candidate address;

[0019] The screening module is used to select the site selection combination scheme with the lowest risk concentration as the site selection result for public infrastructure that can be used for both normal and emergency purposes.

[0020] Beneficial Effects: This application provides a method and system for site selection and screening of public infrastructure suitable for both normal and emergency use. By constructing a graph structure of urban infrastructure, it deeply analyzes the dependence of candidate sites on key upstream infrastructure, quantifies their individual vulnerabilities, and further assesses the common dependency risks of site selection combinations, forming a closed-loop, systematic site selection process. It is precisely this interconnected and progressive analytical approach that enables this application to effectively capture and quantify the "chain reaction" caused by infrastructure failures, thereby selecting site selection schemes for public infrastructure suitable for both normal and emergency use that demonstrate greater resilience in actual emergencies, significantly improving the city's ability to respond to emergencies. Attached Figure Description

[0021] Figure 1 A flowchart illustrating a site selection method for public infrastructure that can be used for both emergency and routine purposes, as provided in this application.

[0022] Figure 2 This is a schematic diagram of a site selection and screening system for public infrastructure that can be used for both emergency and routine purposes, provided in this application.

[0023] Labeling Explanation: 1. Graph Structure Generation Module; 2. Critical Upstream Infrastructure Identification Module; 3. Vulnerability Assessment Module; 4. Site Selection Combination Scheme Acquisition Module; 5. Combination Risk Assessment Module; 6. Screening Module. Detailed Implementation

[0024] The technical model of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0025] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0026] refer to Figure 1 This application proposes a site selection method for dual-use public infrastructure, used to select sites from multiple candidate sites for the construction of dual-use public infrastructure, including the following steps:

[0027] A1. Obtain the connection relationships and functional dependencies of various infrastructures and candidate addresses in the city, and generate a graph structure; each node in the graph structure represents an infrastructure or candidate address, and each edge represents the physical connection or functional dependency between the nodes.

[0028] A2. For each candidate address, based on the graph structure, identify the critical upstream infrastructure that the candidate address depends on;

[0029] A3. For each candidate address, determine the impact of the individual failure of each of the corresponding critical upstream infrastructures on the service capability of the candidate address, quantify the corresponding single vulnerability score, and use it to calculate the comprehensive vulnerability score of the candidate address;

[0030] A4. Based on the preset demand for dual-use facilities, select different combinations of the candidate addresses to form multiple site selection schemes;

[0031] A5. For each of the aforementioned location combination schemes, based on the graph structure, the critical upstream infrastructure, and the comprehensive vulnerability score, analyze the common dependency information of candidate addresses within the location combination scheme on the critical upstream infrastructure, in order to calculate the combined risk concentration of the location combination scheme; the common dependency information represents the association relationship between the critical upstream infrastructure commonly depended on by the candidate addresses within the location combination scheme and the corresponding candidate address;

[0032] A6. Select the site selection combination scheme with the lowest risk concentration as the site selection result for public infrastructure that can be used for both normal and emergency purposes.

[0033] This application constructs a graph structure of urban infrastructure to deeply analyze the dependence of candidate sites on critical upstream infrastructure and quantifies their vulnerability. Furthermore, by assessing the shared dependence risk of different site selection combinations on critical upstream infrastructure, it can effectively capture and quantify the "chain reaction" caused by infrastructure failure, thereby screening out dual-use public infrastructure site selection schemes with higher resilience in complex emergencies, thus making up for the shortcomings of existing methods in addressing infrastructure failure risks.

[0034] The method provided in this application is primarily applied to the field of urban planning and management, aiming to optimize the site selection process for public infrastructure that serves both emergency and non-emergency purposes. In the urban environment, there are various types of infrastructure, such as water supply systems, power grids, transportation hubs, communication facilities, medical institutions, and various public service facilities. These infrastructures are not only physically connected but also have complex functional dependencies. For example, the normal operation of a medical institution may depend on a stable power supply, a smooth transportation network, and reliable communication services.

[0035] In this application, a graph structure refers to a data model in which nodes can represent any infrastructure or potential dual-use facility candidate sites in a city, while edges represent physical connections (e.g., pipes, cables, roads) or functional dependencies (e.g., power supply supporting communication base stations) between these nodes.

[0036] Critical upstream infrastructure refers to infrastructure that is essential to the emergency service function of a specific candidate site (i.e., the emergency service function of the proposed dual-use public infrastructure), and its failure will directly or indirectly affect the service capacity of the candidate site. For example, for a candidate site as an emergency shelter, its critical upstream infrastructure may include municipal pipelines that provide it with water and electricity, and main traffic arteries that ensure the evacuation of people.

[0037] The individual vulnerability score quantifies the impact of a single critical upstream infrastructure failure on the service capability of a candidate address. The comprehensive vulnerability score, on the other hand, takes into account the impact of the failure of all critical upstream infrastructures individually on the candidate address, reflecting the overall vulnerability of the candidate address to upstream infrastructure risks.

[0038] Common dependency information refers to the situation in a given location combination where one or more candidate addresses jointly depend on the same critical upstream infrastructure, revealing potential risk concentration points. For example, some critical upstream infrastructures may be depended on by only a single candidate address, while others may be depended on by multiple candidate addresses simultaneously. Common dependency information contains the correspondence between the critical upstream infrastructure and all candidate addresses that depend on it, and can be represented by data tuples such as: {critical upstream infrastructure number, candidate address 1 number, ..., candidate address n number}, where n is a positive integer.

[0039] Portfolio risk concentration is an indicator that measures the overall risk level of a site selection portfolio. It takes into account the vulnerability of the critical upstream infrastructure that is commonly relied upon, as well as the number and vulnerability of the candidate sites that are commonly relied upon. It aims to identify site selections that may lead to a large-scale decline in service capacity due to the failure of a few critical upstream infrastructures.

[0040] This application provides a method for site selection and screening of public infrastructure that can be used for both emergency and routine purposes, and its specific implementation can be carried out as follows.

[0041] First, in step A1, it is necessary to obtain the connectivity and functional dependencies of various infrastructures and candidate addresses in the city, and generate a graph structure. Each node in this graph structure represents an infrastructure or candidate address, and each edge represents the physical connection or functional dependency between nodes. For example, information on all existing and planned infrastructures (such as substations, water plants, hospitals, roads, communication base stations, etc.) and candidate addresses for both emergency and non-emergency use facilities can be collected through manual surveys, reviewing urban planning maps, analyzing Geographic Information System (GIS) data, or utilizing big data analytics. This information includes their geographical location, type, and capacity. Subsequently, the connectivity between these infrastructures and candidate addresses is established; for example, which substations supply power to which areas, which water plants supply water to which areas, and which roads connect which areas. Simultaneously, the functional dependencies between them are identified; for example, communication base stations depend on power supply, and hospitals depend on both water and power supply. These relationships can be abstracted as edges in a graph, with nodes representing specific infrastructures or candidate addresses. For example, a weighted directed graph can be constructed, where the edge weights can represent dependency strength or connection capacity.

[0042] Secondly, in step A2, for each candidate address, based on the aforementioned graph structure, the critical upstream infrastructure on which the candidate address depends is identified. Specifically, this can be done by starting from each candidate address and tracing back along the functional dependency edges in the graph structure. For example, for a candidate address selected as an emergency shelter, its normal operation requires the support of various resources such as electricity, water supply, and communication. By searching upwards along the dependency chain in the graph structure, substations, water plants, communication base stations, etc., that provide these resource support to the candidate address can be identified. These traced upstream infrastructures are then identified as the critical upstream infrastructure on which the candidate address depends. For example, breadth-first search (BFS) or depth-first search (DFS) algorithms can be used to start from the candidate address node and traverse upwards along all incoming edges (representing dependencies) until the source node or a preset level limit is reached, marking all traversed upstream infrastructure nodes as critical upstream infrastructure.

[0043] Next, in step A3, for each candidate address, the impact of the individual failure of each critical upstream infrastructure on the service capacity of the candidate address is determined, and the corresponding individual vulnerability score is quantified. These individual vulnerability scores are then combined to obtain the overall vulnerability score of the candidate address. For example, scenarios of individual failure of each critical upstream infrastructure can be simulated. When a substation fails, its impact on the power supply to the candidate addresses it depends on is assessed; when a water plant fails, its impact on the water supply to the candidate addresses is assessed. This degree of impact (the degree of direct impact) can be quantified based on a pre-defined assessment model or expert experience. For example, the pre-defined assessment model can be, but is not limited to, an impact matrix-based assessment model. This model uses a two-dimensional matrix to visually represent the impact of failures of different types of critical upstream infrastructure on the expected emergency service functions of candidate sites. The rows of the two-dimensional matrix can represent different types of critical upstream infrastructure (such as electricity, water supply, transportation, and communication), and the columns can represent the expected emergency service functions of candidate sites (such as medical care, supplies, and personnel resettlement). Each cell (i,j) in the two-dimensional matrix stores a pre-defined value, representing the degree of impact of the failure of the i-th type of critical upstream infrastructure on the j-th emergency service function. When a critical upstream infrastructure fails, its impact on various emergency service functions can be obtained by directly consulting the data in the corresponding row of the matrix. For each candidate site, its comprehensive vulnerability score can be obtained by weighted averaging or summing all its individual vulnerability scores to reflect its overall vulnerability to different upstream risks.

[0044] Subsequently, in step A4, based on the preset requirement for the number of dual-use facilities (public and emergency), different combinations of candidate addresses are selected to form multiple site selection schemes. For example, if urban planning requires the construction of three dual-use facilities, then from all candidate addresses that meet the basic conditions, a combination of three addresses can be randomly selected or through a certain combination optimization algorithm to form a site selection scheme. All possible combinations can be generated, or a certain number of representative combination schemes can be generated through heuristic algorithms (such as genetic algorithms or simulated annealing algorithms) to cover different site selection possibilities.

[0045] Further, in step A5, for each location combination scheme, based on the graph structure, critical upstream infrastructure, and comprehensive vulnerability score, the common dependency information of candidate addresses within the location combination scheme on critical upstream infrastructure is analyzed to calculate the combined risk concentration of the location combination scheme. Common dependency information represents the association between the critical upstream infrastructure commonly depended upon by candidate addresses within the location combination scheme and the corresponding candidate address. For example, in a location combination scheme, if two or more candidate addresses within the scheme depend on the same substation, then this substation is the critical upstream infrastructure they commonly depend on. All such common dependencies need to be identified, and it needs to be recorded which candidate addresses commonly depend on which critical upstream infrastructure. Then, combining the vulnerability of the critical upstream infrastructure with the comprehensive vulnerability score and number of candidate addresses commonly depending on it, the risk contribution value of the common dependency relationship is calculated. For example, the more candidate addresses jointly depend on a critical upstream infrastructure, and the higher the comprehensive vulnerability score of these candidate addresses, the greater the risk contribution value of the common dependency relationship. Finally, the risk contribution values ​​of all common dependency information are combined to obtain the combined risk concentration of the location combination scheme.

[0046] Finally, in step A6, the site selection combination with the lowest combined risk concentration is selected as the site selection result for the dual-use public infrastructure. For example, after calculating the combined risk concentration of each of the generated site selection combinations, these combinations are sorted from low to high combined risk concentration. The combination with the lowest combined risk concentration is considered the most resilient and lowest-risk site selection combination, and is thus selected as the final site selection result for the dual-use public infrastructure.

[0047] The method presented in this application aims to address the problem that traditional site selection methods for dual-use public infrastructure fail to adequately consider the vulnerability of urban infrastructure systems and their functional dependencies. This application is effective in solving these problems because it constructs a systematic assessment framework that ranges from macro-network structure to micro-individual vulnerability and then to overall portfolio risk.

[0048] Specifically, firstly, step A1 obtains the connectivity and functional dependencies of various infrastructures and candidate addresses within the city, generating a graph structure. This step is fundamental to the entire method; it abstracts the complex urban infrastructure network into a computable and analyzable data model, enabling subsequent dependency tracing and risk assessment. It is precisely this refined graph structure that makes it possible to quantitatively analyze the complex and intertwined physical connections and functional dependencies between infrastructures, thus overcoming the limitations of traditional methods that treat infrastructure as a static background.

[0049] Secondly, in step A2, for each candidate address, the critical upstream infrastructure it depends on is identified based on the generated graph structure. This process, by tracing the functional dependency chain, accurately locates the supporting infrastructure that is crucial to the emergency service capabilities of the candidate address. It is precisely because these critical upstream infrastructures are identified that the impact of their failure on the candidate address can be assessed in a targeted manner, thus avoiding the drawback of traditional methods that only focus on geographical location and ignore functional dependencies.

[0050] Furthermore, in step A3, for each candidate address, the impact of the individual failure of each critical upstream infrastructure on its service capability is determined, and individual vulnerability scores and comprehensive vulnerability scores are quantified. This step provides an in-depth analysis of the vulnerability of individual candidate addresses to upstream risks. It is precisely because of this quantification of vulnerability that it becomes possible to objectively assess the resilience of candidate addresses under different risk scenarios, providing a quantitative basis for subsequent site selection decisions.

[0051] Building upon this, in step A4, different combinations of candidate addresses are selected to form multiple site selection schemes based on the preset facility quantity requirements. This step provides diverse options for subsequent overall risk assessment.

[0052] Finally, and one of the core innovations of this application, in step A5, for each site selection combination, based on graph structure, critical upstream infrastructure, and comprehensive vulnerability score, the common dependence information of candidate locations within the site selection combination on critical upstream infrastructure is analyzed, and the concentration of combined risk is calculated. This step is crucial for identifying and quantifying the "chain reaction." It is precisely because of the analysis of common dependence information and the calculation of the concentration of combined risk that the potential high risks arising from multiple dual-use facilities jointly relying on a few critical upstream infrastructures can be captured, thus avoiding the shortcomings of traditional methods that only assess individual locations while ignoring the overall risk superposition effect. In this way, site selection combinations that appear independent but actually share vulnerabilities can be identified, thereby effectively avoiding the risk of widespread emergency service capacity paralysis due to the failure of a few critical upstream infrastructures.

[0053] Finally, in step A6, the site selection combination with the lowest concentration of combined risk is selected as the screening result. This step ensures that the selected combination has the highest resilience in the face of the risk of failure of complex infrastructure.

[0054] In summary, this application constructs a graph structure of urban infrastructure, deeply analyzes the dependence of candidate sites on critical upstream infrastructure, quantifies their individual vulnerabilities, and further assesses the shared dependency risks of site selection combinations, forming a closed-loop, systematic site selection process. It is precisely this interconnected and progressive analytical approach that enables this application to effectively capture and quantify the "chain reaction" caused by infrastructure failures, thereby selecting site selection schemes for dual-use public infrastructure with higher resilience in actual emergencies, significantly improving the city's ability to respond to emergencies.

[0055] In some preferred embodiments, step A2 includes:

[0056] A201. Obtain the expected emergency service functions of the candidate address;

[0057] A202. Determine the resource support required for each of the anticipated emergency service functions described above;

[0058] A203. In the graph structure, trace the source node that supports the resource;

[0059] A204. Identify the source node as the critical upstream infrastructure on which the candidate address depends.

[0060] Step A201 aims to define the service capabilities that each candidate site should possess in an emergency. For example, a dual-use public infrastructure might be expected to provide multiple emergency services such as medical assistance, supplies storage, personnel resettlement, or information and communication. These anticipated emergency service capabilities form the basis for assessing its resilience and vulnerability.

[0061] Furthermore, step A202 involves conducting an in-depth analysis of the aforementioned anticipated emergency service functions to determine the various resource supports necessary for their normal operation. Specifically, medical assistance functions generally require resources such as electricity, water, medical equipment, and medicines; material storage functions generally require stable storage space, transportation routes, and security systems; personnel resettlement functions generally require living space, heating / cooling, sanitation facilities, and food supplies; and information and communication functions generally rely on network connectivity, communication equipment, and power supply. These resource supports are fundamental to maintaining emergency service functions.

[0062] Therefore, in step A203, based on the generated graph structure, the identified resource support can be traced to identify the source nodes providing this resource support. Nodes in the graph structure represent infrastructure or candidate addresses, and edges represent physical connections or functional dependencies. By analyzing the connections and functional dependencies in the graph structure, the dependency chain can be traced upwards until the original or critical node providing specific resource support is found. For example, if the medical function of a candidate address requires electricity, it can be traced back to the substation or power plant node supplying it.

[0063] Finally, in step A204, the traced source nodes are identified as critical upstream infrastructure upon which the candidate address depends. These source nodes are defined as critical upstream infrastructure because their normal operation directly or indirectly supports the expected emergency service functions of the candidate address. Failure of these critical upstream infrastructures will directly impact the service capabilities of the candidate address.

[0064] This application's solution refines the expected emergency service functions of candidate sites and further analyzes the specific resource support required for these functions, thereby systematically tracing the sources of these resource supports within a graph structure. This bottom-up, function-to-resource tracing mechanism makes the identification process of critical upstream infrastructure more accurate and comprehensive. By clearly defining functional and resource dependencies, it is possible to clearly identify which infrastructures are indispensable supports for candidate sites in emergency situations, thus laying a solid foundation for subsequent vulnerability assessments and risk analyses.

[0065] The aforementioned technical solution enables the accurate identification of critical upstream infrastructure on which candidate sites for dual-use public infrastructure rely. Compared to identification based solely on physical connections or rough functional classifications, this solution, through in-depth analysis of anticipated emergency service functions and their required resource support, can more comprehensively and accurately reveal the deep dependencies of candidate sites. This helps avoid overlooking implicit dependencies crucial to the service capabilities of candidate sites, thereby improving the accuracy and reliability of subsequent vulnerability assessments and providing stronger data support for the site selection of dual-use public infrastructure.

[0066] In some implementations, step A3 includes:

[0067] A301. Obtain the expected emergency service functions of the candidate address;

[0068] A302. Determine the extent of the impact of the failed critical upstream infrastructure on the expected emergency service functions of the candidate addresses, based on the type of the failed critical upstream infrastructure.

[0069] A303. Based on the degree of impact and the importance of each expected emergency service function, a corresponding individual vulnerability score is obtained by quantification.

[0070] A304. By combining the individual vulnerability scores, a comprehensive vulnerability score for the candidate address is obtained.

[0071] Step A301 aims to clarify the specific functions that a candidate address should possess in an emergency. For example, a candidate address may be expected to provide multiple emergency services such as medical assistance, supplies storage, personnel evacuation, or command and dispatch. These functions form the basis for assessing its service capabilities.

[0072] Furthermore, step A302 involves analyzing failure scenarios of critical upstream infrastructure. When a critical upstream infrastructure (e.g., a water supply system, power grid, communication base station, etc.) fails, its impact on the expected emergency service functions of candidate locations needs to be assessed. The determination of this impact can be based on pre-defined rules, historical data analysis, or expert experience. For example, a power outage may result in the complete loss of medical assistance functions, while a communication outage may only affect the partial efficiency of command and dispatch functions.

[0073] Building on this, step A303 combines the aforementioned impact levels with the importance of each anticipated emergency service function. Different emergency service functions have different priorities and importance in the overall emergency response. For example, life-support medical functions are generally more important than functions providing recreational facilities. By weighting the impact level with functional importance or using non-linear calculations, a single vulnerability score can be quantified for the candidate site in the event of a failure of each critical upstream infrastructure. This ensures that assessments of impairments to high-importance functions have higher weight.

[0074] Finally, step A304 combines the individual vulnerability scores generated by the failure of all critical upstream infrastructure. This combination can be a simple summation, a weighted average, or other aggregation method, designed to comprehensively reflect the overall vulnerability level of the candidate site in the face of failures of different critical upstream infrastructures. This yields a quantitative comprehensive vulnerability score, which is used for subsequent site selection.

[0075] This application's solution refines the vulnerability assessment process for candidate sites into several clearly defined sub-steps, including obtaining expected emergency service functions, determining the degree of failure impact, quantifying individual vulnerability scores, and synthesizing a comprehensive vulnerability score. This achieves a refined quantification of the impact of critical upstream infrastructure failures on the service capabilities of candidate sites. Specifically, firstly, it clarifies the emergency function requirements of candidate sites, laying the foundation for subsequent vulnerability analysis. Secondly, by analyzing the impact of different types of critical upstream infrastructure failures on various emergency functions, potential weaknesses can be identified. Thirdly, by combining the degree of impact with functional importance, it ensures that the assessment results accurately reflect the severity of critical function impairment. Finally, by synthesizing various individual vulnerability scores, it is possible to comprehensively and objectively assess the overall resilience of candidate sites in the face of multiple potential risks, providing reliable data support for subsequent site selection decisions.

[0076] The aforementioned technical solution enables a more comprehensive, detailed, and quantitative assessment of the vulnerability of candidate sites for dual-use public infrastructure. Compared to a rough assessment of service capacity impairment, this solution delves into the impact on specific emergency service functions and weights these impacts based on their importance, making the vulnerability score more instructive. This helps to more accurately identify candidate sites that can maintain high service capacity even in the event of critical upstream infrastructure failure during the site selection process, thereby improving the reliability and emergency response capabilities of the final site selection plan.

[0077] When assessing the site selection of dual-use public infrastructure, determining the impact of critical upstream infrastructure failure on the service capabilities of candidate sites is crucial. It is possible to consider only the direct impact of the failed critical upstream infrastructure on the various anticipated emergency service functions of the candidate site; however, when determining the impact of the failed critical upstream infrastructure on the various anticipated emergency service functions of the candidate site, considering only the direct impact may fail to fully capture the complex interdependencies between the various emergency service functions within the candidate site, resulting in an incomplete or inaccurate assessment of overall vulnerability. For example, the failure of one function may affect other seemingly unrelated service functions through cascading effects; failing to consider this may underestimate the actual risk.

[0078] Therefore, in some possible implementations, step A302 includes:

[0079] Obtain the dependencies between the various expected emergency service functions of the candidate addresses;

[0080] Based on the type of the failed critical upstream infrastructure, determine the directly affected functions and their corresponding degree of direct impact among the expected emergency service functions of the candidate address, which are considered as the degree of impact of the failed critical upstream infrastructure on the directly affected functions.

[0081] Based on the dependencies between the directly affected functions and the various expected emergency service functions, and based on the degree of direct impact, the degree of cascading impact of the failure event on other expected emergency service functions besides the directly affected functions is determined, which is used as the degree of impact of the critical upstream infrastructure failure on the other expected emergency service functions.

[0082] Specifically, the phrase "obtaining the dependencies between the various expected emergency service functions of the candidate addresses" refers to the need for in-depth analysis, during the vulnerability assessment of candidate addresses for dual-use public infrastructure, of whether there are interdependencies among the various emergency service functions (e.g., medical assistance, material reserves, personnel resettlement, information communication, etc.) that the candidate addresses can provide. These dependencies can be functional preconditions, resource sharing, or information transmission. For example, medical assistance may depend on power supply and material reserve functions, while material reserve functions may depend on transportation functions. These dependencies can be analyzed using historical data, functional flowcharts, expert knowledge bases, etc., to construct an internal functional dependency network model.

[0083] The phrase "determining the directly affected functions and their corresponding degrees of direct impact among the expected emergency service functions of the candidate addresses" refers to first identifying which expected emergency service functions will be directly affected by the failure event when a critical upstream infrastructure (e.g., urban power grid, water supply system, communication network, etc.) fails. For example, if the urban power grid fails, functions that rely on electricity, such as lighting, cooling, and information transmission, will be directly affected. The degree of direct impact can be quantified using a pre-set assessment model (e.g., the impact matrix-based assessment model mentioned above) or expert experience.

[0084] In practical applications, the phrase "based on the dependencies between the directly affected functions and various expected emergency service functions, and based on the degree of direct impact, determining the cascading impact of a failure event on other expected emergency service functions besides the directly affected functions" means that after identifying the directly affected functions and their impact levels, the dependencies between the various expected emergency service functions obtained previously are used to further analyze how these direct impacts are transmitted through the functional dependency chain, thereby indirectly affecting other unaffected functions. The calculation of the cascading impact level can be achieved by constructing an impact matrix; the rows and columns of this impact matrix represent the expected emergency service functions of the candidate address, respectively; the element values ​​in the impact matrix represent the dependency strength of the row function on the column function (the dependency strength between various expected emergency service functions can be set through data statistics or expert experience); when a critical upstream infrastructure fails, causing a decrease in the service capacity of one or more directly affected functions, its direct impact level is used as the initial input; subsequently, through matrix multiplication or iterative calculation, this direct impact level is propagated along the functional dependencies within the impact matrix. For example, if the direct impact level of function A is K, and the dependency strength of function B on function A is λ1, then function B will be subject to a cascading impact of K*λ1. If function C depends on function B with a dependency strength of λ2, then function C will be subject to a cascade effect of K*λ1*λ2.

[0085] This application's solution, through meticulous analysis of the dependencies between various anticipated emergency service functions within candidate sites and by distinguishing between directly impacted functions and cascading impacted functions, enables a more comprehensive and accurate assessment of the impact of critical upstream infrastructure failures on the service capabilities of candidate sites. Traditional methods may only focus on direct impacts while neglecting the complex interrelationships between functions, leading to biased vulnerability assessments. This application identifies and quantifies these cascading impacts, making the assessment of the impact on the service capabilities of candidate sites more realistic, thereby avoiding site selection errors caused by underestimating risks.

[0086] The aforementioned technical solution enables a more precise quantification of the impact of critical upstream infrastructure failures on the service capacity of candidate sites for dual-use public infrastructure. This approach not only considers direct impacts but, more importantly, reveals the cascading effects between functions, resulting in a more comprehensive and in-depth vulnerability assessment. This avoids underestimating risks due to neglecting cascading effects, thus providing more reliable and forward-looking data support for site selection and significantly improving the robustness and emergency response capabilities of site selection schemes.

[0087] In some preferred embodiments, a specific example is given below. Suppose a candidate address has three anticipated emergency service functions: power supply, medical assistance, and supplies storage. It is known that the medical assistance function depends on the power supply function, the supplies storage function also depends on the power supply function, and the medical assistance function also depends on the supplies storage function (e.g., refrigerated medicines).

[0088] When this critical upstream infrastructure, the city's power grid, fails:

[0089] First, we need to understand the dependencies between these three functions: the medical assistance function depends on the power supply function; the material reserve function depends on the power supply function; and the medical assistance function depends on the material reserve function.

[0090] Secondly, determine the directly affected functions and the degree of direct impact. The power supply function is directly affected by the failure of the urban power grid, and the degree of direct impact may be 100% (complete interruption).

[0091] Then, based on the directly affected functions (power supply functions) and their degree of impact, as well as the dependencies between functions, the cascading effects are determined.

[0092] Because medical assistance relies on power supply, a power outage will have a cascading impact on medical assistance. Similarly, because material reserves depend on power supply, a power outage will also have a cascading impact on material reserves. Furthermore, since medical assistance also depends on material reserves, if material reserves are damaged due to a power failure, medical assistance will again be affected in a cascading manner. The total impact will be the sum of the direct impact and all cascading effects. In this way, the overall impact of a city power grid failure on the expected emergency service functions of a candidate location can be comprehensively assessed, resulting in a more accurate individual vulnerability score.

[0093] In some embodiments described above in this application, when determining the impact of a single failure of critical upstream infrastructure on the service capability of a candidate site, a single vulnerability score is quantified by combining the degree of impact with the importance of the expected contingency service functions. However, in practical applications, for certain critical contingency service functions, when the impact reaches or exceeds a certain critical point, its impact on the overall service capability may exhibit a non-linear amplification effect. Simple linear or conventional calculation methods may not accurately reflect this sharp increase in risk, resulting in insufficient accuracy in site vulnerability assessment.

[0094] Therefore, in some preferred embodiments, step A303 includes:

[0095] Different impact thresholds are set based on the importance of each anticipated emergency service function;

[0096] Determine whether the impact on each expected emergency service function has reached or exceeded its corresponding impact threshold.

[0097] When the impact of each expected emergency service function reaches or exceeds its corresponding impact threshold, the individual vulnerability score is nonlinearly calculated based on the impact level and the importance level of the emergency service function to reflect the amplification effect after the impact level and the importance of the function are combined.

[0098] When the impact on each expected emergency service function does not reach its corresponding impact threshold, the individual vulnerability score is calculated based on the impact level and the importance level of each expected emergency service function.

[0099] Specifically, setting different impact thresholds means that the maximum impact that different anticipated emergency service functions, such as medical care, material supply, and communication support, can withstand should be differentiated based on their varying importance within dual-use public infrastructure. For example, the impact threshold for life-saving functions might be set lower, meaning that even minor impacts could be considered severe; while for non-core auxiliary functions, the impact threshold might be set higher. These impact thresholds can be determined based on expert experience, historical data, or risk assessment models.

[0100] The determination of whether the impact level reaches or exceeds its corresponding impact threshold aims to identify failure events that may lead to serious consequences. When the impact level reaches or exceeds the impact threshold, it indicates that the service capability of the function has been significantly impaired, requiring more rigorous assessment methods.

[0101] In practical applications, when the impact reaches or exceeds the critical threshold, a nonlinear calculation is performed on the individual vulnerability score to more accurately reflect the amplification effect of the risk. For example, exponential functions, piecewise functions, or other nonlinear models can be used for calculation. This nonlinear calculation ensures that even a small increase in the impact level after exceeding the critical threshold will significantly increase the calculated vulnerability score, thus highlighting the severity of the failure event. The nonlinear calculation incorporates the importance level of emergency service functions, meaning that for more important functions, the amplification effect of their vulnerability score will be more pronounced when their impact exceeds the critical threshold.

[0102] Conversely, when the impact level does not reach its corresponding critical threshold, a conventional calculation method is used, namely, a linear or quasi-linear calculation based on the impact level and the importance of emergency service functions. This indicates that within a controllable range, the increase in risk is relatively stable.

[0103] This application's solution addresses the problem that traditional assessment methods may fail to accurately capture the risk amplification effect of critical functions under severe damage by introducing an impact threshold and distinguishing between nonlinear and linear calculations. Specifically, when the failure of critical upstream infrastructure results in a relatively small impact on expected emergency service functions, not reaching the preset impact threshold, the calculation of individual vulnerability scores uses a conventional method, which aligns with the general law of risk accumulation. However, once the impact reaches or exceeds the impact threshold set for the importance of the function, it means that the function's service capacity has suffered severe damage beyond what is typically expected. At this point, a nonlinear calculation method is adopted, allowing the growth rate of individual vulnerability scores to far exceed the growth rate of the impact, thus significantly amplifying the vulnerability brought about by this severe impact in a quantitative sense. This mechanism ensures that functions crucial to urban operations and the safety of residents' lives and property are assigned higher vulnerability scores when facing severe failure risks, thereby receiving greater priority and avoidance in subsequent site selection.

[0104] Through the aforementioned technical solutions, this application can more accurately and sensitively assess the vulnerability of dual-use public infrastructure sites. Especially when critical emergency service functions face severe impacts, the introduction of impact thresholds and nonlinear calculations effectively captures and quantifies the amplification effect of risks, avoiding the potential underestimation of risks inherent in traditional assessment methods. Consequently, the resulting individual vulnerability scores and comprehensive vulnerability scores more realistically reflect the resilience level of candidate sites under extreme conditions, thus enabling the final selected dual-use public infrastructure site selection schemes to possess higher reliability and robustness in responding to emergencies, significantly enhancing the city's ability to handle transitions between normal and emergency situations.

[0105] Furthermore, the step of performing a nonlinear calculation on the individual vulnerability score based on the degree of impact and the importance level of the emergency service function when the impact of each expected emergency service function reaches or exceeds its corresponding impact threshold, in order to reflect the amplification effect of the combination of impact degree and functional importance, may include:

[0106] The extent to which the degree of influence exceeds the critical point of influence;

[0107] The importance level of the emergency service function is determined based on its importance.

[0108] A nonlinear amplification factor is generated based on the extent to which the degree of impact exceeds the critical point of impact and the importance level of the emergency service function;

[0109] The nonlinear amplification factor is applied to the calculation of the individual vulnerability score to reflect the amplification effect after the degree of impact is combined with the functional importance.

[0110] Specifically, obtaining the extent by which the degree of impact exceeds the critical point refers to quantifying the difference between the actual degree of impact and the preset critical point. For example, if the critical point for the impact of a certain expected emergency service function is set at 20% of the function loss, and the actual assessed degree of impact is 35% of the function loss, then the excess is 15%. This magnitude is a key indicator for measuring whether the degree of functional impairment exceeds the acceptable range; the larger the value, the more severe the functional impairment.

[0111] Specifically, determining the importance level of each emergency service function based on its significance refers to classifying each expected emergency service function into different importance levels according to its criticality in urban operation, emergency response, or public welfare. For example, the importance levels can be divided into multiple tiers such as "extremely high," "high," "medium," and "low." These levels can be determined based on expert experience, historical data analysis, policy and regulatory requirements, or relevant industry standards.

[0112] In practical applications, a nonlinear amplification coefficient is generated based on the extent to which the impact exceeds the critical point and the importance level of the emergency service function. This aims to couple the severity of functional impairment with the criticality of the function itself, generating an amplification factor that reflects the composite risk. For example, a lookup table can be pre-defined, with rows representing the extent of the impact and columns representing the importance level, storing the corresponding pre-defined nonlinear amplification coefficient values. Alternatively, a nonlinear function can be defined, using the extent of the impact as the independent variable and the importance level as the parameter, to calculate and output the corresponding amplification coefficient. Generally, the higher the importance level and the greater the extent of the impact, the larger the generated nonlinear amplification coefficient, reflecting a stronger risk amplification effect.

[0113] Therefore, the nonlinear amplification factor is applied to the calculation of the individual vulnerability score to reflect the amplification effect after the impact level is combined with the functional importance. Specifically, the generated nonlinear amplification factor can be used as a multiplier in the basic individual vulnerability score (the basic individual vulnerability score can be calculated as follows: based on the importance level of the emergency service function, using a preset importance level-importance weight mapping table, the importance weight of the emergency service function is determined, and then the impact level is multiplied by the importance weight to obtain the basic individual vulnerability score). In this way, when the impact level exceeds a critical point, the individual vulnerability score will increase significantly in a nonlinear manner, thereby more realistically reflecting the severity of the damage to the key function and its amplifying effect on the vulnerability of the overall system.

[0114] This application's solution precisely quantifies the severity of functional impairment by obtaining the extent to which the impact exceeds the critical threshold. Simultaneously, by combining the importance level of emergency service functions, it ensures that risk assessments of critical functions receive higher weight. Therefore, based on these two pieces of information, a non-linear amplification coefficient is generated, allowing the calculation of individual vulnerability scores to fully consider the depth of impact and the criticality of functions. This enables the vulnerability score to be amplified non-linearly when the impact exceeds the critical threshold, more accurately reflecting potential cascading effects and systemic risks. It is precisely this refined non-linear amplification mechanism that allows vulnerability assessment results to more realistically reflect the potential risks of dual-use public infrastructure under extreme circumstances.

[0115] Through the aforementioned technical solution, this application enables more refined and accurate nonlinear calculations for individual vulnerability scores. Compared to simply performing general nonlinear calculations, this solution introduces the magnitude of impact exceeding the critical point, the importance level of emergency service functions, and a nonlinear amplification coefficient, allowing vulnerability assessments to more sensitively capture the risk amplification effect when critical functions are damaged beyond expectations. This helps to more accurately identify critical nodes that could lead to systemic collapse in emergency situations, thereby providing a more reliable and forward-looking risk assessment basis for the site selection of dual-use public infrastructure, effectively enhancing the resilience of site selection schemes.

[0116] Specifically, when the impact on each expected emergency service function does not reach its corresponding impact threshold, the individual vulnerability score is calculated based on the impact level and the importance level of each expected emergency service function. The basic individual vulnerability score calculation method mentioned above can be used for calculation, and the calculated basic individual vulnerability score is taken as the valid individual vulnerability score.

[0117] In some implementations, step A5 includes:

[0118] For each critical upstream infrastructure corresponding to the location combination scheme, A501 identifies candidate addresses within the location combination scheme that commonly depend on the critical upstream infrastructure, and obtains a corresponding common dependency information.

[0119] A502. Obtain the vulnerability index of each of the key upstream infrastructures corresponding to the site selection combination scheme;

[0120] A503. For each of the aforementioned common dependency information items, calculate the risk contribution value of the common dependency information based on the vulnerability index of the critical upstream infrastructure corresponding to the common dependency information, the number of candidate addresses corresponding to the common dependency information, and the comprehensive vulnerability score of each candidate address corresponding to the common dependency information.

[0121] A504. Calculate the combined risk concentration of the site selection combination scheme by combining the risk contribution values ​​of the common dependency information mentioned above.

[0122] Step A501 aims to identify the common dependencies of candidate addresses on critical upstream infrastructure within the site selection portfolio. Specifically, for each critical upstream infrastructure in the site selection portfolio, the system iterates through all candidate addresses within the portfolio to identify which candidate addresses commonly depend on that specific critical upstream infrastructure. This common dependency is recorded as common dependency information, which represents the association between the critical upstream infrastructure commonly depended on by the candidate addresses within the site selection portfolio and the corresponding candidate addresses. For example, if multiple candidate addresses depend on the same power supply station, then the power supply station and its associated candidate addresses constitute a common dependency information.

[0123] Step A502 is used to obtain the vulnerability index of each of the critical upstream infrastructures corresponding to the site selection combination scheme. The vulnerability index can be understood as a quantitative assessment of the likelihood of functional impairment or failure of the critical upstream infrastructure when facing potential risks, and the possible consequences. This index can comprehensively consider factors such as the physical condition of the infrastructure, operational stability, maintenance status, and its importance in the entire urban infrastructure network.

[0124] Step A503 aims to quantify the risk contribution of each piece of common dependency information. Specifically, for each identified piece of common dependency information, its risk contribution value is calculated based on the following three core elements: First, the vulnerability index of the critical upstream infrastructure corresponding to the common dependency information, which reflects the risk level of the shared infrastructure itself; second, the number of candidate addresses that commonly depend on the critical upstream infrastructure, with a larger number generally indicating a wider potential impact; and finally, the comprehensive vulnerability scores of these candidate addresses, which reflect the degree of service capability impairment of each candidate address in the event of a failure of the critical upstream infrastructure. By combining these factors, the contribution of the common dependency information to the overall risk of the entire site selection portfolio can be calculated.

[0125] Step A504 aims to calculate the combined risk concentration of the site selection combination. After obtaining the risk contribution values ​​of all common dependencies, these risk contribution values ​​are aggregated to obtain the combined risk concentration of the entire site selection combination. This aggregation can be a simple summation or a complex calculation based on specific weights or aggregation models, with the aim of comprehensively reflecting the overall risk level of the site selection combination due to common reliance on critical upstream infrastructure.

[0126] This application's approach refines the calculation process of combined risk concentration for site selection schemes into steps such as identifying common dependencies, obtaining vulnerability indicators of critical upstream infrastructure, calculating the risk contribution value of common dependencies, and integrating various risk contribution values. This makes the risk assessment of dual-use public infrastructure site selection more systematic and accurate. By clearly identifying the critical upstream infrastructures that multiple candidate sites commonly depend on and quantifying the risks arising from these common dependencies, potential risk concentration points can be effectively revealed. Furthermore, by comprehensively considering the vulnerability of the critical upstream infrastructure itself, the number of candidate sites with common dependencies, and their respective comprehensive vulnerability scores, the calculation of risk contribution values ​​becomes more comprehensive and objective.

[0127] The aforementioned technical solutions enable a more accurate assessment of the overall risk level of different site selection combinations, particularly regarding the potential cascading effects and risk concentration issues that may arise from the failure of critical upstream infrastructure. This meticulous risk assessment helps avoid clustering multiple dual-use facilities with shared vulnerabilities together, thereby reducing the risk of widespread service capacity disruption due to the failure of a single infrastructure element in an emergency. Consequently, the selected dual-use public infrastructure sites will be more resilient and reliable, better able to respond to emergencies, and ensure urban operations and resident safety.

[0128] In some of the above implementations, when calculating the combined risk concentration of a site selection combination, it is necessary to obtain the vulnerability index of each critical upstream infrastructure corresponding to the site selection combination. However, if only this vulnerability index is obtained without fully considering the complex dependencies between critical upstream infrastructures and the cascading failures that may be triggered, the assessment of the true vulnerability of the infrastructure may be incomplete or inaccurate, thereby affecting the reliability of the final site selection results.

[0129] Therefore, in some preferred embodiments, step A502 includes:

[0130] Obtain the dependencies between the key upstream infrastructures;

[0131] To identify the direct failure risk of each of the aforementioned key upstream infrastructures;

[0132] Based on the dependencies between the key upstream infrastructures, identify the other key upstream infrastructures that each key upstream infrastructure corresponding to the location combination scheme depends on;

[0133] For each of the critical upstream infrastructures corresponding to the aforementioned site selection combination scheme, the cascading failure impact is calculated based on the direct failure risk of the other critical upstream infrastructures it depends on.

[0134] For each of the critical upstream infrastructures corresponding to the aforementioned site selection combination scheme, its vulnerability index is calculated by combining its direct failure risk and the impact of cascading failures.

[0135] Specifically, when identifying dependencies between critical upstream infrastructure, these dependencies can include, but are not limited to, physical connections, functional dependencies, information flow dependencies, or resource sharing dependencies. For example, a power substation may functionally depend on a water supply system (for cooling) and a communication network (for remote control).

[0136] Direct failure risk refers to the probability or extent of failure of critical upstream infrastructure due to its own internal faults, aging, or direct external shocks (such as natural disasters or human-caused damage). This risk can be quantified through historical data, expert assessments, or risk models. For example, by collecting operational records of critical upstream infrastructure over a predetermined period (such as five or ten years), the frequency of equipment failures, downtime, and causes of failures can be analyzed; or historical natural disaster data (such as the frequency and intensity of earthquakes, floods, and typhoons) of the geographical location of the critical upstream infrastructure can be combined with a risk assessment report on potential human-caused damage in the region; alternatively, power system experts can be invited periodically to conduct on-site assessments of the aging and maintenance status of substation equipment, and an aging risk level can be assigned based on industry standards and experience, with the most recently determined aging risk level used as the current aging risk level. This data can then be input into a pre-defined risk assessment model, such as fault tree analysis or event tree analysis, to calculate the probability and expected impact of functional interruption of the power substation due to its own causes or direct external shocks, thereby obtaining a quantitative value for its direct failure risk.

[0137] When identifying other critical upstream infrastructures that critical upstream infrastructure depends on, a pre-generated graph structure can be used to trace all direct or indirect dependencies of a critical upstream infrastructure through graph traversal algorithms (such as depth-first search or breadth-first search). For example, if a hospital's critical upstream infrastructure is its power supply, and that power supply depends on a power plant and transmission lines, then the power plant and transmission lines are other critical upstream infrastructures that the hospital depends on.

[0138] Cascading failure impact refers to the chain reaction where the failure of a critical upstream infrastructure can lead to the failure of other related critical upstream infrastructures due to its dependencies on other infrastructures. Calculating cascading failure impact involves assessing how the direct failure risk of other critical upstream infrastructures propagates downstream through dependency chains based on identified dependencies, and quantifying its impact on the function of the target critical upstream infrastructure. For example, a dependency graph can be constructed based on the identified dependencies between critical upstream infrastructures (nodes in the dependency graph represent critical upstream infrastructures, and edges between nodes contain propagation factors, representing the impact of the failure of the upstream node on the downstream node). When a critical upstream infrastructure fails, the dependency graph can be used to identify which dependency chains its impact might propagate downstream through (this can be done using graph traversal algorithms such as depth-first search or breadth-first search), thus tracing all potentially affected critical upstream infrastructures. Dependency chains that include the target critical upstream infrastructure (i.e., the critical upstream infrastructure currently being used to calculate its cascading failure impact) are considered other critical upstream infrastructures on which the target critical upstream infrastructure depends; furthermore, the impact can be further analyzed... For each other critical upstream infrastructure on which the target critical upstream infrastructure depends, the direct failure risk of that other critical upstream infrastructure is calculated as the product of the propagation factor of all edges along the propagation path from that other critical upstream infrastructure to the target critical upstream infrastructure. This yields the corresponding single cascade failure impact (for example, if the direct failure risk of other critical upstream infrastructure A is f, and the propagation factor from other critical upstream infrastructure A to the target critical upstream infrastructure B is c1 and c2 respectively, then the single cascade failure impact of other critical upstream infrastructure A on the target critical upstream infrastructure B is equal to f*c1*c2). Finally, the sum or weighted sum of the single cascade failure impacts corresponding to all other critical upstream infrastructures on which the target critical upstream infrastructure depends is calculated to obtain the cascade failure impact of the target critical upstream infrastructure.

[0139] Ultimately, by comprehensively considering the direct failure risks of critical upstream infrastructure and their cascading failure impacts, a more comprehensive and accurate vulnerability index can be obtained. For example, the vulnerability index can be derived by summing or weighted summing the direct failure risks and the cascading failure impacts. This comprehensive approach reflects the true vulnerability of infrastructure within complex networks, rather than merely its independent risks.

[0140] This application's approach, through in-depth analysis of the complex dependencies between critical upstream infrastructures and quantification of their direct failure risks and cascading failure impacts, enables a more accurate assessment of the vulnerability of each critical upstream infrastructure. This method overcomes the limitations of considering only the risk of a single infrastructure, revealing potential cascading failure risks arising from interdependence, thus making the vulnerability assessment results more closely reflect reality.

[0141] The aforementioned technical solutions enable the acquisition of more accurate vulnerability indicators for critical upstream infrastructure, thereby providing a more accurate reflection of the overall risk faced by the site selection combination in subsequent calculations of combined risk concentration. This helps identify and avoid site combinations that could lead to a significant decline in service capacity due to the vulnerability of critical upstream infrastructure and its cascading effects during the site selection process for dual-use public infrastructure, significantly improving the resilience and reliability of the final site selection and ensuring that infrastructure can continue to provide critical services in emergency situations.

[0142] In some implementations, step A503 includes:

[0143] The sum of the comprehensive vulnerability scores of each candidate address corresponding to the common dependency information is calculated and denoted as the score sum.

[0144] The vulnerability index, the number of candidate addresses, and the total score of the critical upstream infrastructure corresponding to the common dependency information are normalized to obtain normalized vulnerability index, normalized number, and normalized total score.

[0145] Based on preset weighting coefficients, the normalized vulnerability index, the normalization quantity, and the sum of the normalized scores are weighted and aggregated to calculate the risk contribution value of the common dependency information.

[0146] Specifically, the sum of the comprehensive vulnerability scores of all candidate addresses corresponding to the shared dependency information is calculated and denoted as the score sum. This aims to quantify the overall vulnerability level faced by all candidate addresses that share a common dependency on a specific critical upstream infrastructure in the event of a failure. This score sum reflects the cumulative impact on the functionality or service capabilities of these candidate addresses.

[0147] Furthermore, the vulnerability indicators, candidate address counts, and total scores of the critical upstream infrastructure corresponding to the shared dependency information are normalized to obtain normalized vulnerability indicators, normalized counts, and normalized total scores. The purpose of normalization is to eliminate differences in units and numerical ranges between different indicators, ensuring comparability of indicators in subsequent calculations and preventing any single indicator from having an excessively large numerical range that could influence the results. For example, normalization can employ methods such as Min-Max Normalization or Z-score normalization to map the original data to a uniform interval, such as [0, 1] or a distribution with a mean of 0 and a standard deviation of 1.

[0148] Based on this, the normalized vulnerability index, the number of normalized values, and the sum of the normalized scores are weighted and aggregated according to preset weighting coefficients to calculate the risk contribution value of the common dependency information. The preset weighting coefficients reflect the relative importance of different factors (vulnerability of critical upstream infrastructure, number of candidate addresses for common dependency, and cumulative vulnerability of these candidate addresses) in assessing the risk contribution value. For example, these weighting coefficients can be determined based on expert experience, historical data analysis, or simulation results to ensure that the calculated risk contribution value accurately reflects the actual risk situation. Weighted aggregation is typically achieved by multiplying each normalized index by its corresponding weighting coefficient and then summing all products to obtain a comprehensive risk contribution value.

[0149] The proposed solution comprehensively considers the vulnerability of critical upstream infrastructure, the number of candidate addresses with which they are jointly dependent, and the cumulative vulnerability scores of these candidate addresses. By employing normalization and weighted aggregation, it systematically and quantitatively assesses the risk contribution of each piece of jointly dependent information. This approach ensures that the calculation of the combined risk concentration of site selection schemes comprehensively and accurately reflects different risk sources and their impact, avoiding the bias inherent in assessments based on a single indicator.

[0150] The above technical solutions provide a structured and quantifiable method to calculate the risk contribution value of shared dependency information, making the assessment of combined risk concentration more scientific and accurate. This refined risk quantification method helps to more effectively identify and manage potential risks in the site selection of dual-use public infrastructure, thereby providing decision-makers with a more reliable basis for selecting the site combination scheme with the lowest risk and the strongest resilience.

[0151] refer to Figure 2 This application provides a site selection screening system for dual-use public infrastructure, used to screen sites from multiple candidate sites for constructing dual-use public infrastructure. The system includes:

[0152] Graph structure generation module 1 is used to obtain the connection relationships and functional dependencies of various infrastructures and candidate addresses in the city and generate a graph structure; each node in the graph structure represents an infrastructure or candidate address, and each edge represents the physical connection or functional dependency relationship between the nodes (for details, please refer to step A1 above).

[0153] The critical upstream infrastructure identification module 2 is used to identify the critical upstream infrastructure on which each candidate address depends, based on the graph structure (for details, please refer to step A2 above).

[0154] Vulnerability assessment module 3 is used to determine the impact of the individual failure of each of the critical upstream infrastructures on the service capability of the candidate address for each candidate address, and quantify the corresponding single vulnerability score to calculate the comprehensive vulnerability score of the candidate address (the specific process can be referred to step A3 above).

[0155] The site selection combination scheme acquisition module 4 is used to select different combinations of the candidate addresses to form multiple site selection combination schemes based on the preset quantity requirements of dual-use facilities (for details, please refer to step A4 above).

[0156] The combined risk assessment module 5 is used to analyze the common dependence information of candidate addresses within the location combination scheme on the critical upstream infrastructure based on the graph structure, the critical upstream infrastructure, and the comprehensive vulnerability score for each location combination scheme, in order to calculate the combined risk concentration of the location combination scheme; the common dependence information represents the association relationship between the critical upstream infrastructure commonly depended on by the candidate addresses within the location combination scheme and the corresponding candidate address (for details, please refer to step A5 above).

[0157] The screening module 6 is used to select the site selection combination scheme with the lowest risk concentration as the site selection result for public infrastructure that can be used for both normal and emergency purposes (for details, please refer to step A6 above).

[0158] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for selecting sites for dual-use public infrastructure, used to select the final site for dual-use public infrastructure from multiple candidate sites, characterized in that, The method comprises the steps of: A1. obtaining the connection relationship and functional dependency relationship of various infrastructures and candidate addresses in a city, and generating a graph structure; each node in the graph structure represents an infrastructure or a candidate address, and each edge represents a physical connection or a functional dependency relationship between the nodes; A2. For each candidate address, identifying the key upstream infrastructure on which the candidate address depends based on the graph structure; A3. For each candidate address, determining the impact of the failure of each key upstream infrastructure on the service capability of the candidate address, and quantifying the corresponding single vulnerability score to calculate the comprehensive vulnerability score of the candidate address; A4. Selecting different candidate address combinations to form multiple site selection combination schemes according to the preset number of flat and emergency dual-purpose infrastructure requirements; A5. For each site selection combination scheme, analyzing the common dependency information of the candidate addresses in the site selection combination scheme on the key upstream infrastructure based on the graph structure, the key upstream infrastructure, and the comprehensive vulnerability score, to calculate the combination risk concentration degree of the site selection combination scheme; the common dependency information represents the association relationship between the key upstream infrastructure and the corresponding candidate address that are commonly dependent on the candidate addresses in the site selection combination scheme; A6. Selecting the site selection combination scheme with the lowest combination risk concentration degree as the site selection screening result of the flat and emergency dual-purpose public infrastructure; Step A2 comprises: A201. obtaining the expected emergency service functions of the candidate address; A202. determining the resource support required by each of the expected emergency service functions; A203. tracing the source node of the resource support in the graph structure; A204. identifying the source node as the key upstream infrastructure on which the candidate address depends; Step A3 comprises: A301. obtaining the expected emergency service functions of the candidate address; A302. determining the influence degree of the failed key upstream infrastructure on each expected emergency service function of the candidate address according to the type of the failed key upstream infrastructure; A303. quantifying the corresponding single vulnerability score according to the influence degree and the importance of each expected emergency service function; A304. synthesizing the single vulnerability scores to obtain the comprehensive vulnerability score of the candidate address; Step A302 comprises: obtaining the dependency relationship between each expected emergency service function of the candidate address; determining the directly affected function of the candidate address that is directly affected by the failure event and the corresponding direct influence degree as the influence degree of the failed key upstream infrastructure on the directly affected function according to the type of the failed key upstream infrastructure; determining the cascade influence degree of the failure event on other expected emergency service functions except the directly affected function based on the direct influence degree according to the directly affected function and the dependency relationship between each expected emergency service function, as the influence degree of the failed key upstream infrastructure on the other expected emergency service functions.

2. The method of claim 1, wherein, Step A303 comprises: different impact critical points are set according to the importance of each expected emergency service function; determine whether the impact degree of each expected emergency service function reaches or exceeds its corresponding impact critical point; when the impact degree of each expected emergency service function reaches or exceeds its corresponding impact critical point, the single vulnerability score is calculated non-linearly according to the impact degree and the importance level of the emergency service function to reflect the amplification effect of the combination of impact degree and function importance; when the impact degree of each expected emergency service function does not reach its corresponding impact critical point, the single vulnerability score is calculated according to the impact degree combined with the importance level of each expected emergency service function.

3. The method of claim 2, wherein, The step of when the impact degree of each expected emergency service function reaches or exceeds its corresponding impact critical point, the single vulnerability score is calculated non-linearly according to the impact degree and the importance level of the emergency service function to reflect the amplification effect of the combination of impact degree and function importance comprises: obtain the magnitude of the impact degree exceeding the impact critical point; determine the importance level of the emergency service function according to the importance of the emergency service function; generate a non-linear amplification coefficient according to the magnitude of the impact degree exceeding the impact critical point and the importance level of the emergency service function; apply the non-linear amplification coefficient to the calculation of the single vulnerability score to reflect the amplification effect of the combination of the impact degree and the function importance.

4. The method of claim 1, wherein, Step A5 comprises: A501. For each of the critical upstream infrastructures corresponding to the site combination scheme, identify candidate addresses within the site combination scheme that are commonly dependent on the critical upstream infrastructure, to obtain corresponding common dependency information; A502. Obtain the vulnerability index of each of the critical upstream infrastructures corresponding to the site combination scheme; A503. For each of the common dependency information, calculate the risk contribution value of the common dependency information according to the vulnerability index of the critical upstream infrastructure corresponding to the common dependency information, the number of candidate addresses corresponding to the common dependency information, and the comprehensive vulnerability score of each candidate address corresponding to the common dependency information; A504. Integrate the risk contribution values of each of the common dependency information to calculate the combined risk concentration of the site combination scheme.

5. The method of claim 4, wherein, Step A502 comprises: obtain the dependency relationship between the critical upstream infrastructures; obtain the direct failure risk of each of the critical upstream infrastructures; identify other critical upstream infrastructures that each of the critical upstream infrastructures corresponding to the site combination scheme depends on according to the dependency relationship between the critical upstream infrastructures; for each of the critical upstream infrastructures corresponding to the site combination scheme, calculate its cascading failure impact based on the direct failure risk of the other critical upstream infrastructures it depends on; For each of the key upstream infrastructure corresponding to the site combination scheme, the vulnerability index thereof is calculated by synthesizing its direct failure risk and the cascading failure impact.

6. The method of claim 4, wherein, Step A503 includes: calculating the sum of the comprehensive vulnerability scores of each candidate address corresponding to the common dependency information, denoted as score sum; normalizing the vulnerability index of the key upstream infrastructure corresponding to the common dependency information, the number of candidate addresses, and the score sum to obtain a normalized vulnerability index, a normalized number, and a normalized score sum; According to the preset weight coefficient, the normalized vulnerability index, the normalized number, and the normalized score sum are weighted and aggregated to calculate the risk contribution value of the common dependency information.

7. A flat and emergency dual-purpose public infrastructure site selection screening system for screening a final flat and emergency dual-purpose public infrastructure site from a plurality of candidate sites, characterized by, The system comprises: a graph structure generation module configured to obtain connection relationships and functional dependency relationships of various infrastructures and candidate addresses in a city, and generate a graph structure; each node in the graph structure represents an infrastructure or a candidate address, and each edge represents a physical connection or a functional dependency relationship between the nodes; a key upstream infrastructure identification module configured to, for each candidate address, identify key upstream infrastructures relied on by the candidate address based on the graph structure; a vulnerability assessment module configured to, for each candidate address, determine the impact of the individual failure of each key upstream infrastructure on the service capability of the candidate address, and quantitatively obtain a single vulnerability score, which is used to calculate the comprehensive vulnerability score of the candidate address; a site combination scheme acquisition module configured to select different combinations of candidate addresses to form multiple site combination schemes according to a preset number of dual-purpose public infrastructure requirements; a combination risk assessment module configured to, for each site combination scheme, analyze common dependency information of candidate addresses in the site combination scheme on key upstream infrastructures based on the graph structure, the key upstream infrastructures, and the comprehensive vulnerability scores, and calculate a combination risk concentration degree of the site combination scheme; the common dependency information represents the association between key upstream infrastructures commonly relied on by the candidate addresses in the site combination scheme and the corresponding candidate addresses; a screening module configured to select the site combination scheme with the lowest combination risk concentration degree as a site screening result of the dual-purpose public infrastructure; The key upstream infrastructure identification module, when identifying, for each candidate address, key upstream infrastructures relied on by the candidate address based on the graph structure, performs: A201. obtaining expected emergency service functions of the candidate address; A202. determining resource support required by each of the expected emergency service functions; A203. tracing source nodes of the resource support in the graph structure; A204. identifying the source nodes as key upstream infrastructures relied on by the candidate address; The vulnerability assessment module, when determining, for each of the candidate addresses, the impact of individual failure of each of the critical upstream infrastructure on service capability of the candidate address, quantifying a corresponding single-item vulnerability score, and using the single-item vulnerability score to calculate a comprehensive vulnerability score of the candidate address, performs: A301. obtaining expected emergency service functions of the candidate address; A302. determining, according to a type of the failed critical upstream infrastructure, an influence degree of the failed critical upstream infrastructure on each of the expected emergency service functions of the candidate address; A303. quantifying a corresponding single-item vulnerability score according to the influence degree and in combination with importance of each of the expected emergency service functions; A304. synthesizing the single-item vulnerability scores to obtain a comprehensive vulnerability score of the candidate address; Step A302 comprises: obtaining dependency relationships among the expected emergency service functions of the candidate address; determining, according to the type of the failed critical upstream infrastructure, a directly-affected function of the expected emergency service functions of the candidate address that is directly affected by the failure event and a corresponding direct influence degree, as the influence degree of the failed critical upstream infrastructure on the directly-affected function; determining, according to the directly-affected function and the dependency relationships among the expected emergency service functions, a cascading influence degree of the failure event on other expected emergency service functions of the candidate address that are not the directly-affected function, as the influence degree of the failed critical upstream infrastructure on the other expected emergency service functions, based on the direct influence degree.

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