A method and system for dividing nuclear emergency planning areas based on spatial data analysis

Abstract

The present invention discloses a method and system for dividing nuclear emergency planning areas based on spatial data analysis, including: collecting nuclear power plant geospatial data and performing preprocessing. Analyzing the preprocessed spatial data to identify key factors affecting nuclear emergency response. Identifying and dividing regional importance according to the key factors. Evaluating the risks of each key area and formulating emergency response plans. The method and system for dividing nuclear emergency planning areas based on spatial data analysis provided by the present invention calculate the impact factor of population density, the normalized complexity score of land use types, and the exponential impact factor of the transportation network within a specific area, achieving an accurate assessment of the importance of each sub-area. Calculating risk scores for key areas and formulating emergency response plans based on the comprehensive risk scores. Through this systematic process of risk assessment and emergency response plan formulation, the scientificity and effectiveness of nuclear emergency response are ensured, and the accuracy and efficiency of emergency management are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of spatial data analysis, and particularly to a method and system for dividing nuclear emergency planning areas based on spatial data analysis. Background Art

[0002] With the increase in the number of nuclear power plants globally and the continuous improvement of energy demand, nuclear energy, as an efficient and clean energy source, has been widely used. However, the occurrence of nuclear accidents not only causes serious environmental pollution but also poses a huge threat to public health and social stability. Therefore, how to quickly and effectively implement emergency responses in the event of a nuclear accident and minimize the impact of nuclear radiation on people and the environment has become an urgent problem for governments and nuclear power plant operators around the world.

[0003] Existing nuclear emergency response systems mainly rely on pre-established emergency plans and command and dispatch systems. These systems are usually designed based on historical data and experience and have some deficiencies in practical applications. First, existing emergency plans often lack pertinence and real-time nature and cannot fully consider the complex and changeable environmental factors during nuclear accidents. Second, most traditional emergency response systems are based on static data and fail to make full use of modern spatial data analysis technology, making it impossible to timely and accurately evaluate and predict the scope and degree of accident impacts. In addition, existing systems also have limitations in resource allocation and evacuation route planning and are difficult to make optimal decisions quickly in case of emergencies. Therefore, developing a method for dividing nuclear emergency planning areas based on spatial data analysis to improve the scientificity and effectiveness of nuclear emergency responses has important practical significance. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that most traditional emergency response systems rely on static data and cannot timely and accurately evaluate and predict the scope and degree of accident impacts. The present invention adopts modern spatial data analysis technology and comprehensively analyzes various types of dynamic spatial data through methods such as integral calculation, normalized complexity scoring, and exponential impact factors, realizing precise assessment and prediction of accident impacts and making up for the limitations of static data analysis. Traditional emergency response methods often have difficulty comprehensively considering multiple influencing factors, resulting in one-sided emergency decisions. The present invention comprehensively collects and analyzes terrain data, land use data, population distribution data, transportation network data, and infrastructure data, comprehensively evaluates various risk factors, ensures the scientificity and comprehensiveness of emergency decisions, and improves the accuracy and effectiveness of emergency responses.

[0006] 1 To solve the above technical problems, the present invention provides the following technical solutions: A method for dividing nuclear emergency planning areas based on spatial data analysis, comprising: collecting nuclear power plant geospatial data and performing preprocessing.

[0007] Analyze the preprocessed spatial data to identify key factors affecting nuclear emergency response.

[0008] Identify and divide the regional importance according to the key factors.

[0009] Evaluate the risks of each key area and formulate an emergency response plan.

[0010] 2 As a preferred embodiment of the method for dividing nuclear emergency planning areas based on spatial data analysis according to the present invention, wherein: the collecting of nuclear power plant geospatial data and performing preprocessing includes collecting topographic data, land use data, population distribution data, transportation network data, and infrastructure data.

[0011] Data preprocessing includes data cleaning, removing noise from the data, and filling missing values with the average value of the data before and after.

[0012] 3 As a preferred embodiment of the method for dividing nuclear emergency planning areas based on spatial data analysis according to the present invention, wherein: the analyzing of the preprocessed spatial data to identify key factors affecting nuclear emergency response includes calculating the influence factor of population density in a specific area through integration, and the integrated influence factor of geographical location and population density is expressed as:

[0013]

[0014] Wherein, I1 represents the integrated influence factor of geographical location and population density, ρ(x,y) represents the population density at location (x,y), d(x,y) represents the distance between location (x,y) and the nuclear power plant, λ represents the scale parameter of the attenuation factor, and A represents the integration area.

[0015] The normalized complexity of land use types is expressed as:

[0016]

[0017] Wherein, I2 represents the normalized complexity score of land use types, L i represents the area of the i-th land use type, T i represents the complexity coefficient of the i-th land use type, 1 for residential areas, 2 for industrial areas, 3 for farmland, 4 for forests, 5 for grasslands, 6 for water bodies, and n represents the number of land use types.

[0018] Calculate the transportation network influence factor through traffic flow, road capacity, and passing speed, expressed as:

[0019]

[0020] Among them, I3 represents the exponential impact factor of the transportation network, and V k represents the traffic flow of the k-th road, and C k represents the road capacity of the k-th road, and C max represents the maximum road capacity among all roads, and S k represents the passing speed of the k-th road, and m represents the number of roads.

[0021] The total key factor score is expressed as:

[0022]

[0023] Among them, K represents the key factor score.

[0024] 4 As a preferred solution of the method for dividing nuclear emergency plan areas based on spatial data analysis according to the present invention, wherein: the identifying and dividing the regional importance according to the key factors includes dividing the area around the nuclear power plant into equal areas according to the influence range of the nuclear power plant, forming a plurality of sub-areas with equal areas.

[0025] Calculate the key factor score for each sub-area. The higher the score value, the greater the importance of the area in the nuclear emergency response. The area with K>0.7 is regarded as the key area.

[0026] 5 As a preferred solution of the method for dividing nuclear emergency plan areas based on spatial data analysis according to the present invention, wherein: the evaluating the risks of each key area includes calculating multiple risk factors for the key area, including population density risk factor, land use risk factor, transportation network risk factor, infrastructure risk factor, and calculating the comprehensive risk score by synthesizing the calculation results of each risk factor.

[0027] 6 As a preferred solution of the method for dividing nuclear emergency plan areas based on spatial data analysis according to the present invention, wherein: the calculation formula of the population density risk factor is expressed as:

[0028]

[0029] Among them, R popadj represents the population density risk factor, ρ(x,y) represents the population density at the position (x,y), α represents the attenuation coefficient, indicating the influence of distance on the risk. d(x,y) represents the distance between the position (x,y) and the nuclear power plant, and A represents the integration area.

[0030] SVI represents the correction of the social vulnerability index, which is expressed as:

[0031]

[0032] Among them, SVI i represents the social vulnerability index of the i-th key area, E i represents the economic condition index of the i-th key area, E max represents the maximum value of the economic condition index among all key areas, M i represents the medical condition index of the i-th key area, M max represents the maximum value of the medical condition index among all key areas, Ai represents the resident age structure index of the i-th key area, A max represents the maximum value of the resident age structure index among all key areas.

[0033] The final calculation formula of the population density risk factor is expressed as:

[0034]

[0035] Among them, R popadj is the population density risk factor, and N represents the number of key areas.

[0036] The calculation formula of the land use risk factor is expressed as:

[0037]

[0038] Among them, R land represents the land use risk factor, L i represents the area of the i-th type of land use, C i represents the risk type coefficient of the i-th type of land use, T i represents the complexity coefficient of the i-th type of land use, and n represents the number of land use types.

[0039] The initial calculation formula of the traffic network risk factor is expressed as:

[0040]

[0041] Among them, R traffic represents the initial traffic network risk factor, V k represents the traffic flow of the k-th road, C k represents the road capacity of the k-th road, C max represents the maximum road capacity among all roads, S k represents the passing speed of the k-th road, and m represents the number of roads.

[0042] Introduce a traffic congestion index correction, which is expressed as:

[0043]

[0044] Among them, TCI j represents the traffic congestion index of the j-th sub-region, V j represents the traffic flow of the j-th sub-region, C j represents the road capacity of the j-th sub-region, T j represents the actual travel time of the j-th sub-region, T free represents the ideal travel time without congestion.

[0045] The final calculation formula of the traffic network risk factor is expressed as:

[0046]

[0047] Among them, R trafficadj represents the traffic network risk factor.

[0048] The calculation formula of the infrastructure risk factor is expressed as:

[0049]

[0050] Among them, R infra represents the infrastructure risk factor, I p represents the importance coefficient of the p-th infrastructure, E p represents the capacity of the p-th infrastructure, D p represents the distance between the p-th infrastructure and the nuclear power plant, and q represents the number of infrastructures.

[0051] The calculation formula of the comprehensive risk assessment is expressed as:

[0052]

[0053] Among them, R total represents the comprehensive risk score.

[0054] 7 As a preferred solution of the method for dividing the nuclear emergency plan area based on spatial data analysis described in the present invention, wherein: the formulation of the emergency response plan includes, according to R total value to divide the risk area, R total the calculation result value range is between 0 and 2. When R total > 1.5, it is a high-risk area. When 0.75 <R total ≤ 1.5, it is a medium-risk area. When R total ≤ 0.75, it is a low-risk area.

[0055] The emergency response plan for high-risk areas prioritizes the allocation of sufficient emergency resources, including rescue teams, medical equipment, evacuation vehicles, and material reserves. Detailed evacuation routes and plans are formulated to ensure that non-essential personnel can evacuate quickly and safely. Multiple evacuation assembly points are set up, and dedicated transportation means are arranged for evacuation.

[0056] The emergency response plan for medium-risk areas allocates appropriate emergency resources to ensure rapid availability when needed. Emphasis is placed on the preparation of medical facilities and the deployment of transportation means. A preliminary evacuation plan is formulated and adjusted according to the actual situation during a nuclear emergency. Evacuation assembly points are set up, and emergency transportation means are arranged.

[0057] The emergency response plan for low-risk areas maintains appropriate emergency resource reserves to ensure basic emergency support during emergencies. Resource reserves include basic medical supplies and a small number of emergency transportation means. A simple evacuation plan is formulated to ensure orderly evacuation during a nuclear emergency. The main evacuation assembly point is set up.

[0058] 8 A nuclear emergency plan area division system based on spatial data analysis, characterized by comprising:

[0059] A preprocessing module that collects the geospatial data of the nuclear power plant and performs preprocessing.

[0060] An analyzed data module that analyzes the preprocessed spatial data and identifies the key factors affecting nuclear emergency response.

[0061] An area division module that identifies and divides the importance of areas according to the key factors.

[0062] A risk assessment module that assesses the risks of each key area and formulates an emergency response plan.

[0063] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method described above are implemented.

[0064] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps of the method described above are implemented.

[0065] The beneficial effects of the present invention: By calculating the impact factor of population density, the normalized complexity score of land use type, and the exponential impact factor of the transportation network in a specific area, the precise assessment of the importance of each sub-area is realized. The comprehensive risk score is calculated for each key area, and an emergency response plan is formulated based on the comprehensive risk score. Through this systematic risk assessment and emergency response plan formulation process, the scientificity and effectiveness of nuclear emergency response are ensured, and the accuracy and efficiency of emergency management are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0067] Figure 1 It is the overall flowchart of a method for dividing nuclear emergency planning areas based on spatial data analysis provided by the first embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0068] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific embodiments of the present invention in detail with reference to the drawings of the specification. Obviously, the described embodiments are some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0069] Embodiment 1

[0070] Refer to Figure 1 , which is an embodiment of the present invention, and provides a method for dividing nuclear emergency planning areas based on spatial data analysis, including:

[0071] S1: Collect the geospatial data of the nuclear power plant and perform preprocessing.

[0072] Collect land use data, population distribution data, transportation network data, and infrastructure data.

[0073] The land use is the land use type.

[0074] The population distribution data includes population density, total population, and population age structure.

[0075] The transportation network data includes road type, road density, and traffic flow.

[0076] The infrastructure data includes the geographical locations and capacities of hospitals, schools, emergency shelters, fire stations, hydropower stations, and communication base stations.

[0077] The data preprocessing includes data cleaning, removing the noise in the data, and filling the missing values with the average values of the data before and after.

[0078] S2: Analyze the preprocessed spatial data and identify the key factors affecting nuclear emergency response.

[0079] The impact factor of population density within a specific area is calculated through integration. The integrated impact factors of geographical location and population density are expressed as:

[0080]

[0081] Among them, I1 represents the integrated impact factor of geographical location and population density, ρ(x, y) represents the population density at location (x, y), d(x, y) represents the distance between location (x, y) and the nuclear power plant, λ represents the scale parameter of the attenuation factor, and A represents the integration area.

[0082] It should be noted that this formula calculates the impact factor of population density within a specific area through integration and takes into account the attenuation effect of distance. The farther the distance, the smaller the impact. Therefore, an exponential decay function is adopted. The integration area A is the influence range of the nuclear power plant.

[0083] The normalized complexity of land use types is expressed as:

[0084]

[0085] Among them, I2 represents the normalized complexity score of land use types, L i represents the area of the i-th land use type, T i represents the complexity coefficient of the i-th land use type, which is 1 for residential areas, 2 for industrial areas, 3 for farmland, 4 for forests, 5 for grasslands, 6 for water bodies, and n represents the number of land use types.

[0086] It should be noted that this formula scores by calculating the normalized area ratio of different land use types and combining their complexity coefficients. A sine function is used to adjust the complexity coefficients to ensure the non-linear impact of complexity on the score.

[0087] Furthermore, each complexity coefficient is historical experimental data and can be modified manually.

[0088] The impact factor of the transportation network is calculated through traffic flow, road capacity, and passing speed, and is expressed as:

[0089]

[0090] Among them, I3 represents the exponential impact factor of the transportation network, V k represents the traffic flow of the k-th road, C k represents the road capacity of the k-th road, C max represents the maximum road capacity among all roads, S k represents the passing speed of the k-th road, and m represents the number of roads.

[0091] It should be noted that this formula calculates the influence factor of the traffic network through three parameters: traffic flow, road capacity, and passing speed. The combination of the logarithmic function and the exponential decay function reflects the non-linear relationship between traffic flow and capacity, as well as the weakening of the influence by speed.

[0092] The total key factor score is expressed as:

[0093]

[0094] Among them, K represents the key factor score.

[0095] S3: Identify and divide the regional importance according to the key factors.

[0096] The area around the nuclear power plant is divided into multiple sub-regions of equal area according to the influence scope of the nuclear power plant.

[0097] Calculate the key factor score for each sub-region. The higher the score value, the greater the importance of the region in the nuclear emergency response. The region with K>0.7 is regarded as the key region.

[0098] S4: Evaluate the risks of each key region and formulate emergency response plans.

[0099] Calculate the risk factors in multiple aspects for the key region, including population density risk factor, land use risk factor, traffic network risk factor, and infrastructure risk factor. Integrate the calculation results of each risk factor to calculate the comprehensive risk score.

[0100] The calculation formula of the population density risk factor is expressed as:

[0101]

[0102] Among them, R popadj represents the population density risk factor, ρ(x,y) represents the population density at the location (x,y), α represents the attenuation coefficient, indicating the influence of distance on the risk. d(x,y) represents the distance between the location (x,y) and the nuclear power plant, and A represents the integration region.

[0103] SVI represents the correction of the social vulnerability index, which is expressed as:

[0104]

[0105] Among them, SVI i represents the social vulnerability index of the i-th key region, E i represents the economic status index of the i-th key region, E max represents the maximum value of the economic status index among all key regions, M i represents the medical condition index of the i-th key region, Mmax represents the maximum value of the medical condition index among all key areas, and \(A_i\) represents the resident age structure index of the \(i\)-th key area, \(A\) max represents the maximum value of the resident age structure index among all key areas.

[0106] The final calculation formula of the population density risk factor is expressed as:

[0107]

[0108] where \(R\) popadj is the population density risk factor, and \(N\) represents the number of key areas.

[0109] It should be noted that the population density risk factor calculates the impact of population density in a specific area through integration. Combining the distance decay effect, the areas closer to the nuclear power plant contribute more to the risk. In order to more accurately reflect the vulnerability of each area, the Social Vulnerability Index (SVI) is introduced, which comprehensively considers factors such as economic status, medical conditions, and resident age structure for weighted correction. It can comprehensively evaluate the population distribution in different areas and its impact on nuclear emergency response. By considering the distance decay and the social vulnerability index, the formula can not only identify areas with high population density but also highlight those areas with high social vulnerability even though the population density is low. This can ensure that emergency resources and measures can better cover the areas in need and improve the accuracy and effectiveness of emergency response.

[0110] The calculation formula of the land use risk factor is expressed as:

[0111]

[0112] where \(R\) land represents the land use risk factor, \(L\) i represents the area of the \(i\)-th land use type, \(C\) i represents the risk type coefficient of the \(i\)-th land use type, \(T\) i represents the complexity coefficient of the \(i\)-th land use type, and \(n\) represents the number of land use types.

[0113] The land use risk factor normalizes different land use types and scores them in combination with their complexity and risk type. It can accurately evaluate the impact of various land use types in the area on emergency response. By considering the complexity and risk type of land use, the formula can identify high-risk land use types, such as residential areas and industrial areas, which require more emergency resources and attention. This factor helps to optimize resource allocation, improve the efficiency of emergency response, and ensure that high-risk areas can be given priority treatment.

[0114] Furthermore, each complexity coefficient is historical experimental data and can be modified manually.

[0115] The initial calculation formula of the traffic network risk factor is expressed as:

[0116]

[0117] Among them, R traffic represents the initial traffic network risk factor, V k represents the traffic flow of the k-th road, C k represents the road capacity of the k-th road, C max represents the maximum road capacity among all roads, S k represents the passing speed of the k-th road, and m represents the number of roads.

[0118] Introduce a traffic congestion index correction, which is expressed as:

[0119]

[0120] Among them, TCI j represents the traffic congestion index of the j-th sub-region, V j represents the traffic flow of the j-th sub-region, C j represents the road capacity of the j-th sub-region, T j represents the actual driving time of the j-th sub-region, T free represents the ideal driving time without congestion.

[0121] The final calculation formula of the traffic network risk factor is expressed as:

[0122]

[0123] Among them, R trafficadj represents the traffic network risk factor.

[0124] It should be noted that the traffic network risk factor calculates the index impact factor of the traffic network by analyzing parameters such as traffic flow, road capacity, and passing speed, and is corrected in combination with the traffic congestion index (TCI). The formula considers the ratio of traffic flow to road capacity and the ratio of actual driving time to ideal driving time, reflecting the saturation degree of the road and the impact of real-time traffic conditions on emergency response. It can comprehensively evaluate the complexity of the traffic network and potential traffic congestion situations. By combining the traffic congestion index, the formula can identify areas prone to traffic congestion, which may become bottlenecks in nuclear emergency response. The introduction of the traffic network risk factor can help optimize evacuation routes and emergency resource allocation, ensuring that the traffic network can effectively support rapid evacuation and rescue in the event of a nuclear emergency and improving the overall efficiency of emergency response.

[0125] The calculation formula for the infrastructure risk factor is expressed as:

[0126]

[0127] Among them, R infra represents the infrastructure risk factor, I p represents the importance coefficient of the p-th infrastructure, E p represents the capacity of the p-th infrastructure, D p represents the distance between the p-th infrastructure and the nuclear power plant, and q represents the number of infrastructures.

[0128] It should be noted that the infrastructure risk factor calculates its risk factor by evaluating the importance coefficient, capacity, and distance from the nuclear power plant of various infrastructures (such as hospitals, schools, emergency shelters, etc.). The formula adopts the method of weighted average, combines the importance and capacity of the infrastructure, and reflects its key role in emergency response. It can comprehensively evaluate the role and importance of various infrastructures in nuclear emergency response. By considering the importance and capacity of the infrastructure, the formula can identify the distribution of key infrastructures and ensure that these facilities can play the greatest role in emergency response. The introduction of the infrastructure risk factor can help optimize resource allocation and emergency response plans, improve the scientificity and effectiveness of emergency management, and ensure that various key infrastructures can be fully utilized and protected in the event of a nuclear emergency.

[0129] The calculation formula for the comprehensive risk assessment is expressed as:

[0130]

[0131] Among them, R total represents the comprehensive risk score.

[0132] According to the value of R total , the risk area is divided. The value range of the calculation result of R total is between 0 and 2. When R total > 1.5, it is a high-risk area. When 0.75 < R total ≤ 1.5, it is a medium-risk area. When R total ≤ 0.75, it is a low-risk area.

[0133] The emergency response plan for the high-risk area is to prioritize the allocation of sufficient emergency resources, including rescue teams, medical equipment, evacuation vehicles, and material reserves, formulate detailed evacuation routes and plans to ensure that irrelevant personnel can evacuate quickly and safely. Set up multiple evacuation assembly points and arrange dedicated transportation for evacuation.

[0134] The emergency response plan for medium-risk areas allocates appropriate emergency resources to ensure rapid activation when needed. It focuses on the preparation of medical facilities and the allocation of transportation vehicles. A preliminary evacuation plan is formulated and adjusted according to the actual situation during a nuclear emergency. Evacuation assembly points are set up, and emergency transportation vehicles are arranged.

[0135] The emergency response plan for low-risk areas maintains an appropriate reserve of emergency resources to ensure basic emergency support during emergencies. The resource reserve includes basic medical supplies and a small number of emergency transportation vehicles. A simple evacuation plan is formulated to ensure an orderly evacuation during a nuclear emergency. The main evacuation assembly points are set up.

[0136] In the above embodiments, there is also a nuclear emergency plan area division system based on spatial data analysis, specifically:

[0137] A preprocessing module collects the geospatial data of the nuclear power plant and performs preprocessing.

[0138] An analysis data module analyzes the preprocessed spatial data to identify the key factors affecting nuclear emergency response.

[0139] A division area module identifies and divides the regional importance according to the key factors.

[0140] A risk assessment module assesses the risks of each key area and formulates an emergency response plan.

[0141] The computer device can be a server. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data cluster data of the power monitoring system. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. The computer program, when executed by the processor, implements a method.

[0142] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0143] Embodiment 2

[0144] An embodiment of the present invention provides a method and system for dividing a nuclear emergency planning area based on spatial data analysis. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0145] A 50-square-kilometer area around a certain nuclear power plant was selected as the test area, and this area was divided into sub-areas of equal area, with each sub-area being 1 square kilometer. Topographic data, land use data, population distribution data, transportation network data, and infrastructure data were collected and preprocessed. These data include topographic elevation values, land use types, population density, total population, population age structure, road types, road density, traffic flow, geographical locations and capacities of hospitals, schools, emergency shelters, fire stations, hydropower stations, and communication base stations.

[0146] The data preprocessing steps include data cleaning, noise removal, and filling of missing values to ensure the high quality and consistency of the data. In data cleaning, the missing values are filled with the average values of the front and back data, and the data format is standardized to ensure that the data can be accurately used in subsequent analyses. The preprocessed spatial data was analyzed to identify the key factors affecting nuclear emergency response. Based on the identified key factors, importance identification and classification were carried out for each sub-area. By calculating the key factor scores of each sub-area, the areas with score values higher than 0.7 were regarded as key areas. These key areas require key attention and resource investment in nuclear emergency response.

[0147] For each key area, multi-faceted risk factors were calculated, including population density risk factor, land use risk factor, transportation network risk factor, and infrastructure risk factor. And based on the calculation results of each risk factor, the comprehensive risk score was calculated. According to the value range of the comprehensive risk score, the test area was divided into high-risk areas, medium-risk areas, and low-risk areas, and corresponding emergency response plans were formulated. The experimental results are shown in Table 1.

[0148] Table 1 Experimental Results

[0149]

[0150]

[0151] Through the above data, detailed risk assessments and comparative analyses were carried out for each sub-area.

[0152] First of all, the influencing factors of population density vary significantly in different regions. The population density in Region E is the highest, at 1,500 people per square kilometer, while the density in Region B is the lowest, only 500 people per square kilometer. High-population-density areas require more resources and more detailed evacuation plans in nuclear emergency response.

[0153] The land use complexity coefficient shows that the complexity in Region E is the highest, at 3.0, while the complexity in Region G is the lowest, only 1.5. High-complexity land use types (such as industrial areas and residential areas) require more attention and resource allocation in emergency response.

[0154] The comprehensive analysis of traffic flow, road capacity, and passing speed shows that the traffic flow in Region E is the highest, reaching 900 vehicles per hour. However, its road capacity and passing speed are relatively low, resulting in a relatively high traffic congestion index of 0.85. Similarly, the traffic flow in Region G is the lowest, only 300 vehicles per hour, and its road capacity and passing speed are relatively high. Therefore, its traffic congestion index is relatively low, at 0.5. These data indicate that the importance of the traffic network in emergency response cannot be ignored, especially in areas with high traffic flow and low capacity, where traffic congestion is more likely to occur, affecting the efficiency of emergency rescue.

[0155] The analysis of the social vulnerability index shows that the social vulnerability indices of Regions E and F are relatively high, at 0.9 and 0.8 respectively, while the index of Region G is the lowest, only 0.3. High-social-vulnerability regions require special attention in nuclear emergency response to ensure that vulnerable groups can receive timely assistance.

[0156] The comprehensive risk score calculated by integrating the above factors shows that the comprehensive risk score of Region E is the highest, exceeding 1.5, belonging to the high-risk region. The comprehensive risk scores of Regions C and F are between 0.75 and 1.5, belonging to the medium-risk regions, while the scores of Regions B and G are lower than 0.75, belonging to the low-risk regions.

[0157] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for dividing nuclear emergency planning areas based on spatial data analysis, characterized in that Including: Collecting the geospatial data of the nuclear power plant and performing preprocessing; Analyzing the preprocessed spatial data to identify the key factors affecting nuclear emergency response; Identifying and dividing the regional importance according to the key factors; The identifying and dividing the regional importance according to the key factors includes dividing the area around the nuclear power plant into equal-sized sub-regions according to the influence scope of the nuclear power plant; Calculating the key factor score for each sub-region. The higher the score value, the greater the importance of the region in nuclear emergency response. The regions with K>0.7 are regarded as key regions; Wherein, K represents the key factor score; Evaluating the risks of each key region and formulating an emergency response plan; The analyzing the preprocessed spatial data to identify the key factors affecting nuclear emergency response includes calculating the influence factor of population density in a specific area through integration. The integrated influence factor of geographical location and population density is expressed as: Wherein, I1 represents the integrated influence factor of geographical location and population density, ρ(x,y) represents the population density at location (x,y), d(x,y) represents the distance between location (x,y) and the nuclear power plant, λ represents the scale parameter of the attenuation factor, and A represents the integration area; The normalized complexity of land use type is expressed as: Among them, I2 represents the normalized complexity score of land use types, and L i represents the area of the i-th land use type, and T i represents the complexity coefficient of the i-th land use type, which is 1 for residential areas, 2 for industrial areas, 3 for farmland, 4 for forests, 5 for grasslands, 6 for water bodies, and n represents the number of land use types; Calculating the traffic network influence factor through traffic flow, road capacity and passing speed, which is expressed as: Among them, I3 represents the exponential influence factor of the traffic network, V k represents the traffic flow of the k-th road, C k represents the road capacity of the k-th road, C max represents the maximum road capacity among all roads, S k represents the passing speed of the k-th road, and m represents the number of roads; The total key factor score is expressed as: Wherein, K represents the key factor score.

2. The method for dividing nuclear emergency planning zones based on spatial data analysis according to claim 1, wherein: The collecting the geospatial data of the nuclear power plant and performing preprocessing includes collecting topographic data, land use data, population distribution data, traffic network data, and infrastructure data; Data preprocessing includes data cleaning, removing the noise in the data, and filling the missing values with the average value of the data before and after; 3. The method for dividing nuclear emergency planning areas based on spatial data analysis according to claim 2, wherein: The evaluating the risks of each key region includes calculating multiple risk factors for the key region, including population density risk factor, land use risk factor, traffic network risk factor, and infrastructure risk factor, and calculating the comprehensive risk score by synthesizing the calculation results of each risk factor; The calculation formula of the population density risk factor is expressed as: Among them, R popadj represents the population density risk factor, ρ(x, y) represents the population density at the location (x, y), d(x, y) represents the distance between the location (x, y) and the nuclear power plant, A represents the integration region, and N represents the number of key regions; SVI represents the correction of the social vulnerability index, which is expressed as: Among them, SVI i represents the social vulnerability index of the i-th key area, E i represents the economic condition index of the i-th key area, E max represents the maximum value of the economic condition index among all key areas, M i represents the medical condition index of the i-th key area, M max represents the maximum value of the medical condition index among all key areas, A i represents the resident age structure index of the i-th key area, A max represents the maximum value of the resident age structure index among all key areas; The calculation formula of the land use risk factor is expressed as: Among them, R land represents the land use risk factor, L i represents the area of the i-th type of land use, C i represents the risk type coefficient of the i-th type of land use, T i represents the complexity coefficient of the i-th type of land use, and n represents the number of land use types; The initial calculation formula of the traffic network risk factor is expressed as: Among them, R traffic represents the initial traffic network risk factor, V k represents the traffic flow of the k-th road, C k represents the road capacity of the k-th road, C max represents the maximum road capacity among all roads, S k represents the passing speed of the k-th road, and m represents the number of roads; Introducing a traffic congestion index correction, which is expressed as: Among them, TCI j represents the traffic congestion index of the j-th sub-region, V j represents the traffic flow of the j-th sub-region, C j represents the road capacity of the j-th sub-region, T j represents the actual travel time of the j-th sub-region, T free represents the ideal travel time without congestion; The final calculation formula of the traffic network risk factor is expressed as: Among them, R trafficadj represents the traffic network risk factor; The calculation formula of the infrastructure risk factor is expressed as: Among them, R infra represents the infrastructure risk factor, I p represents the importance coefficient of the p-th infrastructure, E p represents the capacity of the p-th infrastructure, D p represents the distance between the p-th infrastructure and the nuclear power plant, and q represents the number of infrastructures; The calculation formula of the comprehensive risk assessment is expressed as: Among them, R total represents the comprehensive risk score.

4. The method for dividing nuclear emergency planning areas based on spatial data analysis according to claim 3, wherein: Said formulating an emergency response plan includes dividing risk areas according to the value of R total The value of R total The calculated result value range is between 0 and 2. When R total > 1.5, it is a high-risk area; When 0.75 < R total ≤ 1.5, it is a medium-risk area; when R total ≤ 0.75, it is a low-risk area; The emergency response plan for high-risk regions is to prioritize the allocation of sufficient emergency resources, including rescue teams, medical equipment, evacuation vehicles and material reserves, formulating detailed evacuation routes and plans to ensure that irrelevant personnel can evacuate quickly and safely; setting up multiple evacuation assembly points and arranging dedicated transportation for evacuation; The emergency response plan for medium-risk regions is to allocate appropriate emergency resources to ensure that they can be quickly mobilized when needed, focusing on the preparation of medical facilities and the deployment of transportation; formulating a preliminary evacuation plan and adjusting it according to the actual situation during nuclear emergency events, setting up evacuation assembly points and arranging emergency transportation; The emergency response plan for low-risk areas is to maintain an appropriate reserve of emergency resources to ensure basic emergency support during emergencies; the resource reserve includes basic medical supplies and a small number of emergency transportation vehicles; a simple evacuation plan is formulated to ensure an orderly evacuation in the event of a nuclear emergency; and main evacuation assembly points are set up.

5. A nuclear emergency plan area division system based on spatial data analysis using the method according to any one of claims 1-4, characterized in that: A preprocessing module that collects the geospatial data of the nuclear power plant and performs preprocessing; An analysis data module that analyzes the preprocessed spatial data and identifies the key factors affecting nuclear emergency response; A region division module that identifies and divides the regional importance according to the key factors; A risk assessment module that assesses the risks of each key region and formulates an emergency response plan.

6. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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