Decision-making method for dynamic strike plan based on adaptive matching of ammunition and target

Abstract

The present invention discloses a decision-making method for a dynamic strike plan based on the adaptive matching of ammunition and targets, including: establishing a functional model of the urban system: extracting regional geographical information, combining with the location information of key nodes, and establishing a functional model of the urban system; establishing a database of weapon strike damage effects: integrating multi-dimensional and multi-target weapon strike damage effect data and protection technology data, and establishing a database of weapon strike damage effects; establishing a multi-layer functional model of the system: establishing a sub-system functional association model according to the functional components of the system, integrating multi-dimensional system state information, and establishing a multi-layer functional model of the system; calculating the strike cost-effectiveness: evaluating the damage of the system function and estimating the cost of the strike plan; making a decision on the strike plan: planning the optimal ammunition usage plan according to the ammunition performance, target type, and protection level, and dynamically selecting the optimal strike plan according to the best cost-effectiveness of the key infrastructure under the strike index. The strike plan decision-making method of the present invention is more comprehensive and accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of battlefield assessment, and in particular to a decision-making method for a dynamic strike plan based on adaptive matching of ammunition and targets. Background Art

[0002] Due to the development of information technology, higher requirements are put forward for the combat methods of modern warfare, such as the rapid assessment of system function damage and the dynamic planning of ammunition use. The former is the basis for real-time and effective strikes, and the latter is the guarantee for achieving efficient strikes. They are the main factors for wartime commanders to plan and make decisions. Therefore, there is an urgent need for a rapid matching technology for ammunition use and target damage to improve the decision-making of strike plans.

[0003] Currently, for the technology of optimizing strike plans, most attention is paid to multi-target strike plans in a joint strike environment, and the influence of the surrounding environment on the strike effect is explored.

[0004] The Chinese invention patent application "Method for Establishing a Real-Time Joint Strike Optimization Model" (Application No.: CN202110290487.1, Publication Date: 2021.08.06) discloses a method for establishing a real-time joint strike optimization model, including: obtaining a data set for establishing a joint strike optimization model, the data set including weather environment data, target feature data, interception equipment data, and the occlusion relationship between the target and the interception equipment, and the interception equipment including laser equipment, radio equipment, and flexible net equipment; respectively establishing spatial dimension constraints, time dimension constraints, resource dimension constraints, weather dimension constraints, and environmental dimension constraints for each interception equipment according to the data set; establishing an interception weight factor according to these constraints, and establishing a joint strike optimization model according to the interception weight factor. This method improves the feasibility of the strike plan result in terms of model establishment, but mainly focuses on single-type targets and lacks the optimal decision-making of strike plans that are generally applicable to the entire regional system.

[0005] Chinese invention patent application "Method for Rapid Evaluation of the Feasibility of Multi - target Strike Missions" (Application No.: CN202310364835.4, Publication Date: April 7, 2023) discloses a method for rapid evaluation of the feasibility of multi - target strike missions, including the following steps: Based on the strike plan list and the force resource list, establish a constraint model for the feasibility analysis and evaluation of multi - target strike missions; According to the established constraint model for the feasibility analysis and evaluation of multi - target strike missions, with the minimum number of exceeded resources as the optimization goal, construct a feasibility evaluation model for multi - target strike missions; Solve the feasibility evaluation model of multi - target strike missions based on an improved genetic algorithm to obtain the mission feasibility conclusion. Although this method has a certain connotation of adaptive matching of ammunition and targets, due to a large number of assumptions, such as resource availability and target accessibility, problems that do not conform to the actual situation may occur. In addition, the so - called multi - target only evaluates the feasibility of strike missions from the perspective of quantity, and still lacks decision - making techniques for strike plans considering aspects such as the damage of the overall system function and cascading effects.

[0006] In summary, the problems existing in the prior art are: The decision - making of strike plans is not comprehensive enough, only considering single - type targets and lacking decision - making of strike plans based on the regional system scope; At the same time, the strike plans are not precise enough and do not involve considerations of the cascading of the system function of the strike area. Summary of the Invention

[0007] The purpose of the present invention is to provide a dynamic strike plan decision - making method based on the adaptive matching of ammunition and targets, which is more comprehensive and precise.

[0008] The technical solution for achieving the purpose of the present invention is as follows:

[0009] A dynamic strike plan decision - making method based on the adaptive matching of ammunition and targets, including the following steps:

[0010] (10) Establishment of the urban system function model: Extract regional geographical information from the geographic information system, and combine the location information of key nodes to establish an urban system function model;

[0011] (20) Establishment of the weapon strike damage effect database: Integrate multi - dimensional multi - target weapon strike damage effect data collected from multiple channels and protection technology data collected from multiple channels to establish a weapon strike damage effect database;

[0012] (30) Establishment of the multi - layer system function model: According to the system function components, establish a subsystem function association model, and integrate multi - dimensional system state information to establish a multi - layer system function model;

[0013] (40) Calculation of strike cost - effectiveness: According to the hierarchical relationship of the system function, evaluate the damage of the system function and estimate the cost of the strike plan;

[0014] (50) Strike plan decision-making: According to the ammunition performance, target type, and protection level, plan the optimal ammunition usage plan, and dynamically select the optimal strike plan based on the best cost-effectiveness ratio of critical infrastructure under the set strike indicators.

[0015] Further, the steps for establishing the (20) weapon strike damage effect database include:

[0016] (21) Damage effect data collection: Collect weapon strike damage effect data covering various weapon types and multiple damage modes, including experimental data, historical accident data, and computer simulation data;

[0017] (22) Protection technology data collection: Collect protection technology data from test data, historical materials, and simulation data;

[0018] (23) Database establishment: Preprocess, classify, and integrate the damage effect data and protection technology data, and enter them into the database system to establish a weapon strike damage effect database.

[0019] Further, the steps for establishing the (30) system function multi-layer model include:

[0020] (31) System function component confirmation: Confirm the mutual influence and linkage effect between system function components, including physical association, geographical association, network association, and logical association between each subsystem;

[0021] (32) Subsystem function association model establishment: According to the mutual influence and linkage effect between each subsystem, use the system dynamics modeling method to establish a subsystem function association model for each critical infrastructure;

[0022] (33) Multi-dimensional system state information integration: Map the multi-dimensional system state information of the evaluation object to each system layer, and simulate the interaction and function transfer between each system layer;

[0023] (34) Function multi-layer model establishment and evaluation: Establish a system function multi-layer model with inter-layer connections, and evaluate and determine the key impact chains and system weak points.

[0024] Further, the steps for calculating the (40) strike cost-effectiveness include:

[0025] (41) System function damage assessment: According to the critical facility strike indicators, evaluate the infrastructure integrity and function integrity, and evaluate the system function damage;

[0026] (42) Strike plan cost estimation: According to the system function damage data, estimate the weapon and ammunition costs, deployment and launch costs, logistics and support costs, and determine the strike plan cost.

[0027] Furthermore, the decision-making steps for the (50) strike plan include:

[0028] (51) Ammunition usage planning: According to the type and equivalent of ammunition, combined with the target type, distribution, and protection level, plan the detonation points and explosion methods;

[0029] (52) Selection of the optimal strike plan: Dynamically select the optimal strike plan according to the best cost-effectiveness ratio of critical infrastructure under the set strike indicators.

[0030] Compared with the prior art, the significant advantages of the present invention are:

[0031] 1. The strike plan is more comprehensive: By establishing an explosion shock damage effect database, the present invention can comprehensively analyze the impact of multi-dimensional weapon strike events on the system. Different from the traditional method that only focuses on a single damage effect, the present invention covers a comprehensive assessment of physical damage, functional loss, and their cascading effects, providing more comprehensive protection decision support.

[0032] 2. The strike plan is more accurate: The present invention significantly improves the efficiency in data collection, storage, and analysis through a unified management system for multi-type data. This efficient data management system supports the integration of multi-source data, ensuring the comprehensiveness and accuracy of the data, thereby enhancing the scientific nature of strike plan decision-making. Through system function component analysis, the present invention can accurately evaluate the damage of individual subsystems and reveal the mutual influence and linkage effects between subsystems. By constructing a multi-layer model of system functions, the assessment accuracy of the overall system function loss is further improved. The present invention uses genetic algorithms and dynamic programming methods to establish a strike plan decision-making model for the adaptive matching of ammunition and targets. This model can provide multiple alternative plans based on multi-objective optimization and select the optimal strike strategy with the highest total benefit and the lowest risk through dynamic adjustment. Through real-time data feedback and dynamic programming techniques, the present invention realizes the real-time adjustment of the strike plan. This feature not only improves the execution efficiency of the plan but also ensures rapid response according to environmental changes during actual operation, minimizing losses and optimizing the strike effect to the greatest extent.

[0033] The following further describes the present invention in detail with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is the main flowchart of the dynamic strike plan decision-making method based on the adaptive matching of ammunition and targets of the present invention.

[0035] Figure 2 is Figure 1 the flowchart of the establishment steps of the weapon strike damage database in

[0036] Figure 3 isFigure 1 Flow chart of the steps for establishing the multi - layer model of the system functions in the middle

[0037] Figure 4 Yes Figure 1 Flow chart of the steps for calculating the combat effectiveness and cost in the middle Specific implementation manners

[0038] As Figure 1 shown, the dynamic strike plan decision - making method based on the adaptive matching of ammunition and target of the present invention includes the following steps:

[0039] (10) Establishment of the urban system function model: Extract the regional geographical information from the Geographic Information System (GIS), and combine it with the location information of key nodes to establish an urban system function model; the key nodes include roads, bridges, power stations, oil depots, and reservoirs.

[0040] The virtualized urban system function model is used for subsequent simulation and evaluation.

[0041] Establishing the urban system function model is prior art and will not be elaborated herein.

[0042] (20) Establishment of the weapon strike damage effect database: Integrate the multi - dimensional multi - target weapon strike damage effect data collected from multiple channels and the protection technology data collected from multiple channels to establish a weapon strike damage effect database.

[0043] The weapon strike damage database includes the weapon strike damage data of multi - functional nodes at the urban system level with or without protection measures.

[0044] The weapon strike damage database is used for querying the functional loss situation of each subsequent node.

[0045] As Figure 2 shown, the steps of the (20) establishment of the weapon strike damage effect database include:

[0046] (21) Collection of damage effect data: Collect weapon strike damage effect data covering various weapon types and various damage modes, including experimental data, historical accident data, and computer simulation data.

[0047] By collecting data from multiple channels such as experimental data, historical accident data, and computer simulation data, and these data cover various weapon types and various damage modes, comprehensively obtain weapon strike damage effect data from multi - dimensional strikes and multi - target attacks;

[0048] For example, the source of experimental data can be explosion tests, etc., the source of historical accident data can be industrial explosion records, etc., and the source of computer simulation data can be the simulation results of Abaqus, etc.

[0049] ​Weapon types, such as fuel-air explosive bombs, penetration bombs, fragmentation and blast bombs, thermobaric bombs, and other types of ammunition;

[0050] Target damage modes. Different weapon types cause direct damage such as collapse, deformation, and penetration to components of urban core nodes such as buildings, bridges, and tunnel shelters, as well as secondary damage such as electromagnetic pulses and high-temperature combustion to functional nodes such as electronic devices and communication facilities.

[0051] (22) Collection of protection technology data: Collect protection technology data from test data, historical materials, and simulation data.

[0052] The protection technology data involves three-dimensional desensitization cascade structures, high-temperature and high-resistance structures, and camouflage protection technologies; it also includes a variety of advanced protection materials and structural designs, such as high-performance composite material fiber-reinforced polymers, ultra-high-performance concrete, etc., energy-absorbing protection structures, specifically designed walls, foundations, and support structures, the use of metal grids and energy-absorbing layers, the establishment of protective walls and isolation barriers, etc.;

[0053] (23) Database establishment: Preprocess, classify, and fuse the damage effect data and protection technology data, and enter them into the database system to establish a weapon strike damage effect database.

[0054] Before entering the database system, first unify the ambiguity, difference, and heterogeneity of the data in terms of structure and semantics.

[0055] The steps of the (23) database establishment include:

[0056] (231) Data preprocessing: Remove or correct outliers, standardize feature values, and normalize the data;

[0057] Extract the feature vector X = [x1, x2, …, xn] from the original data, standardize the feature values so that they are on the same scale, and use Min-Max or Z-score normalization, depending on the type and distribution of the data.

[0058] (232) Data feature classification and fusion: Use a convolutional neural network to classify and fuse the data features;

[0059] (233) Data entry: Enter the data into the database system to establish a weapon strike damage effect database.

[0060] The present invention comprehensively evaluates physical damage, functional loss, and their cascading effects on the system by collecting and integrating multi-source and multi-type data, including historical data, experimental data, and numerical simulation data, covering various ammunition types and target damage effects, improving the accuracy of the strike plan and the comprehensiveness of decision support.

[0061] (30)Establishment of the multi - layer system function model: Based on the system function components, establish the subsystem function correlation model, integrate multi - dimensional system status information, and establish the multi - layer system function model.

[0062] Based on the node function loss data in the database and comprehensively considering the multi - dimensional strike damage effects, establish the logical relationships and linkage effects between different systems, such as the function correlations between key infrastructures such as power systems, water supply systems, fuel / gas systems, transportation systems, and communication systems. Adopt an aggregation method based on information, physics, and applications to quantify the overall blast resistance toughness of the system.

[0063] Such as Figure 3 As shown, the steps of the (30) establishment of the multi - layer system function model include:

[0064] (31)Confirmation of system function components: Confirm the mutual influence and linkage effects between system function components, including the physical connection, geographical connection, network connection, and logical connection between each subsystem;

[0065] The steps of the (31) confirmation of system function components include:

[0066] (311)Identification of physical connection: Identify the physical connections between systems and evaluate their relevance;

[0067] Identify and evaluate the physical connections between systems, such as the energy supply relationship between the power system and the dispatching control center. Collect and collate the physical connection data of the facilities to ensure the integrity and accuracy of the data;

[0068] (312)Identification of key positions: According to the layout and mutual dependence of each infrastructure in terms of geographical location, identify the key positions in the urban system function model;

[0069] (313)Identification of network connection: According to the roles of the information and control networks between systems in emergency situations, identify the key communication nodes and control centers;

[0070] Evaluate the information and control networks between systems, especially their roles in emergency situations. Identify the key communication nodes and control centers and analyze their importance in maintaining system functions;

[0071] (314)Establishment of logical connection: Based on the logical relationships and linkage effects between different systems, establish the logical connection model.

[0072] Analyze the logical relationships and linkage effects between different systems, such as the dependence of the water supply system on the power system. By converting various objects into relationships, such as one - to - one recursive relationships, one - to - two binary relationships, one - to - many binary relationships, etc., establish the logical connection model to simulate the linkage reactions between systems under different conditions.

[0073] (32)Establishment of subsystem function correlation model: According to the mutual influence and linkage effect among subsystems, a system dynamics modeling method is adopted to establish a subsystem function correlation model for each critical infrastructure.

[0074] Subsystems include power systems, water supply systems, fuel / gas systems, transportation systems, and communication systems.

[0075] (33)Integration of multi-dimensional system state information: Map the multi-dimensional system state information of the evaluation object to each system layer, and simulate the interaction and function transfer among system layers.

[0076] The multi-dimensional system state information of the evaluation object includes geographical information and node information.

[0077] The integration of multi-dimensional system state information can provide a comprehensive view of the system state and support function evaluation under complex conditions;

[0078] (34)Establishment and evaluation of multi-layer function model: Establish a multi-layer system function model with inter-layer connections, and evaluate and determine the key impact chains and system weak points.

[0079] This step quantifies the impact of explosion shock events on each critical infrastructure and provides accurate quantitative indicators for loss assessment;

[0080] The step of (34) establishment and evaluation of multi-layer function model includes:

[0081] (341)Multi-layer model construction: Establish a multi-layer system function model including the integrity of system infrastructure and function integrity;

[0082] It is stated that the multi-layer system function model can be comprehensively evaluated by combining physical damage data and function loss data;

[0083] (342)Determination of key impact chain and system weak points: According to the function interaction and influence path among system layers in the multi-layer system function model, determine the key impact chains and system weak points.

[0084] By analyzing the dependencies of each system, establish physical, geographical, and network correlation models to achieve the purpose of evaluating system weak points. This method accurately evaluates the damage of individual subsystems, reveals the linkage effect among systems, helps to more comprehensively understand the vulnerability and key nodes of the overall system, and thus optimizes the strike plan.

[0085] (40)Calculation of strike cost-effectiveness: According to the system function hierarchical relationship, evaluate the damage of system functions and estimate the cost of the strike plan.

[0086] By quantitatively reflecting the impact of the strike operation on the functions of the target system, evaluating the cost and effectiveness of the strike plan, and providing reliable basic data support for strike decision-making and budget planning;

[0087] As Figure 4 shown, the (40) strike cost-effectiveness calculation steps include:

[0088] (41) System function damage assessment: According to the critical facility strike indicators, evaluate the infrastructure integrity and function integrity, and evaluate the system function damage;

[0089] The (41) system function damage assessment steps include:

[0090] (411) Setting of critical facility strike indicators: According to ammunition, human resources, and strategic requirements. Set the critical infrastructure strike indicators in the target area;

[0091] According to the identified critical infrastructure in the target area, such as substations, water treatment plants, major transportation hubs, etc. Determine the specific strike indicators for each facility according to requirements, such as the percentage of power supply capacity reduction, the amount of water treatment capacity loss, the reduction in traffic flow, etc.;

[0092] (412) Physical layer damage assessment: According to the infrastructure integrity and function integrity, determine the system integrity and obtain the physical layer damage data.

[0093] Among them, the infrastructure integrity is determined by calculating the health status of each facility according to the following formula,

[0094] ,

[0095] In the formula, is the facility health status of subsystem , is the weight coefficient, is the health value, is the infrastructure node set of this subsystem.

[0096] Adopt the weight coefficient and the health value to weight each facility to form the infrastructure integrity index . Evaluate the function integrity from aspects such as the energy reserve and output capacity of the energy supply system (electricity, water supply, fuel / gas), and the line damage degree, transportation efficiency, and communication coverage of the service system (transportation, communication);

[0097] (413) System function damage assessment: Map the physical layer damage data into the system function multi-layer model to obtain the system function damage data.

[0098] Using multi-dimensional system status information, further conduct system function damage assessment to identify functional and geographical damages caused by a strike event.

[0099] (42) Strike plan cost estimation: Based on the system function damage data, estimate the costs of weapons and ammunition, deployment and launch, logistics and support, and determine the cost of the strike plan.

[0100] Guided by the results of system function damage assessment, provide accurate estimates of the procurement costs of weapons and ammunition to help decision-makers understand the composition of each cost and the main driving factors;

[0101] The steps of the (42) strike plan cost estimation include:

[0102] (421) Weapon and ammunition cost estimation: Based on the system function damage data, determine the types and quantities of required weapons and ammunition, including high-tech equipment such as conventional ammunition, guided weapons, and drones, and estimate the market prices;

[0103] (422) Deployment and launch cost estimation: Based on the types and quantities of the weapons and ammunition, estimate the deployment and launch costs, including transportation, launcher setup and operation, and labor costs;

[0104] Refine the time and resource requirements for each operation step to ensure the accuracy of cost estimation.

[0105] (423) Logistics and support cost estimation: Based on the deployment and launch costs, estimate the logistics support costs required during the execution of the strike mission, such as fuel, communication, and the costs of logistics personnel;

[0106] (424) Determination of the relationship between cost elements and total cost: Use a decision tree neural network model to determine the relationship between cost elements and the total cost.

[0107] By recursively splitting the data set, select the feature that maximally reduces the cost variance as the splitting point to establish a decision tree model.

[0108] (425) Identification of the most influential factor: Based on the importance of each cost element in the decision tree, identify the cost element that has the greatest impact on the total cost.

[0109] (50) Strike plan decision-making: Based on the ammunition performance, target type, and protection level, plan the optimal ammunition usage plan, and dynamically select the optimal strike plan according to the best cost-effectiveness ratio of critical infrastructure under the set strike indicators.

[0110] Based on the type of the target (such as military base, communication center, energy facility, etc.) and the protection level, select the appropriate type of ammunition; make matching decisions on the target type and node function to maximize the strategic and tactical benefits of the strike;

[0111] The described (50) strike plan decision-making steps include:

[0112] (51) Ammunition usage planning: According to the type and equivalent of ammunition, combined with the target type, distribution, and protection level, plan the detonation points and explosion methods;

[0113] Planning the ammunition usage plan is to optimize the usage efficiency of ammunition and ensure that the selected ammunition can effectively achieve the expected effect of the strike mission;

[0114] The described (51) ammunition usage planning steps include:

[0115] (511) Select the type of ammunition: Refer to the destructive power, penetration ability, and effectiveness against specific targets recorded in the database to select the type of ammunition to be used;

[0116] (512) Determine the ammunition equivalent: According to the evaluation results, consider the structural strength, location, and protection measures of the target, and the explosion equivalent required for each target to determine the ammunition equivalent sufficient to achieve the expected damage effect;

[0117] (513) Calculate the amount of ammunition used: Calculate the required amount of ammunition according to the size, shape, and distribution of the target;

[0118] For example, for multiple scattered small targets, multiple small ammunition may be required; for a single large target, a small amount of high-equivalent ammunition may be used;

[0119] (514) Detonation point analysis and explosion method optimization: Dynamically match the ammunition strike characteristics and target damage characteristics, determine the ammunition detonation point according to the strike index and target structure damage response, and determine the best detonation method according to the target information extracted from the geographic information system, including target characteristics and the scene where the target is located;

[0120] By accurately calculating the detonation point and optimizing the detonation method (such as air burst, contact detonation, delayed detonation) according to the target characteristics (such as type, protection measures, dynamics) and scene characteristics (such as surface, underground, cluster, scattered), the damage effect can be maximized and the collateral damage can be minimized.

[0121] (52) Selection of the optimal strike plan: Dynamically select the optimal strike plan according to the best cost-effectiveness ratio of the critical infrastructure under the set strike index.

[0122] Clarify the key targets of the strike and improve the strategic and tactical benefits of the strike;

[0123] The described (52) optimal strike plan selection steps include:

[0124] (521) Identify critical infrastructure: Identify critical infrastructure according to the importance of each infrastructure in the urban system function model, and label it as a critical node;

[0125] Urban critical infrastructure, such as substations, water supply facilities, major transportation hubs, etc. Identify these critical infrastructures based on their importance in the urban system and label them as critical nodes.

[0126] (522) Set strike indicators: Set specific strike indicators for each critical facility according to human, weapon, ammunition resources and strategic needs. At the same time, evaluate the potential impact of the strike on the overall system based on the destruction results of the critical facility nodes and the chain reactions shown in the multi-layer model of system functions;

[0127] The strike indicators such as the proportion of function decline (the percentage of power supply capacity decline) and the degree of physical damage (the degree of structural damage).

[0128] (523) Optimization of cost-effectiveness ratio: Take the cost-effectiveness ratio as the objective function, maximize the strike benefit, use the feasibility and economy of the plan as the constraints, generate multiple strike plans using the genetic algorithm, and evaluate the fitness of each plan;

[0129] (524) Dynamic programming and path optimization: Decompose the strike decision-making process into multiple stages. Each stage makes dynamic programming decisions based on the current state and possible future states, analyzes the state transition possibilities and effects of each stage, and evaluates the benefits and risks of different decision-making paths;

[0130] (525) Selection of the optimal strike plan: Compare the benefits and risks of each decision-making path, select the path with the highest total benefit and the lowest risk to form the optimal strike plan.

[0131] The present invention combines the genetic algorithm and the dynamic programming method to establish a multi-objective optimization model, realizes the adaptive matching of ammunition use and targets, dynamically adjusts the strike strategy in the decision-making process, enables the strike plan to flexibly adapt to the changes in the battlefield environment, and selects the plan with the maximum benefit and the minimum risk. This self-adaptability greatly improves the flexibility of decision-making and the efficiency of strike operations.

[0132] Through the real-time data feedback mechanism, the decision-making system is allowed to make dynamic adjustments according to the actual situation, ensuring that in the actual combat environment, decision-makers can quickly adjust the strategy to cope with emergencies and environmental changes, thereby minimizing the risks brought by uncertainties and optimizing the strike effect.

Claims

1. A dynamic strike plan decision method based on adaptive matching of ammunition and target, characterized in that: The steps include: (10) Establishment of urban system functional model: Extract regional geographic information from the geographic information system and combine it with key node location information to establish an urban system functional model; (20) Establishment of a database on weapon strike damage effects: Integrate multi-dimensional and multi-target weapon strike damage effects data collected from multiple channels, as well as protection technology data collected from multiple channels, to establish a database on weapon strike damage effects; (30) Establishment of multi-layer model of system function: According to the system function components, establish the subsystem function association model, integrate the multi-dimensional system status information, and establish the multi-layer model of system function; (40) Calculation of strike effectiveness and cost: Based on the hierarchical relationship of system functions, evaluate the damage to system functions and estimate the cost of the strike plan; (50) Strike plan decision-making: Plan the optimal ammunition use plan based on ammunition performance, target type and protection level, and dynamically select the optimal strike plan based on the best cost-effectiveness of key infrastructure under the set strike indicators; The (30) system function multi-layer model establishment step includes: (31) Confirmation of system functional components: Confirm the mutual influence and linkage effects between system functional components, including the physical, geographical, network and logical connections between subsystems; (32) Establishment of subsystem functional correlation model: Based on the mutual influence and linkage effect between subsystems, a subsystem functional correlation model is established for each key infrastructure using system dynamics modeling; (33) Multi-dimensional system status information integration: Map the multi-dimensional system status information of the evaluation object to each system layer, and simulate the interaction and function transfer between each system layer; (34) Functional multi-layer model establishment and evaluation: Establish a multi-layer model of system functions with inter-layer connections, and evaluate and determine the key impact chains and system weaknesses; The (31) system functional component confirmation step includes: (311) Physical connection identification: identifying the physical connections between systems and assessing their relevance; (312) Identification of key locations: Identification of key locations in the functional model of the urban system based on the geographical layout and interdependence of the infrastructure; (313) Network association identification: Identification of key communication nodes and control centers based on the role of information and control networks between systems in emergency situations; (314) Logical association establishment: Establish a logical association model based on the logical relationship and linkage effect between different systems; The (34) functional multi-layer model establishment and evaluation steps include: (341) Multi-layer model construction: Establish a multi-layer model of system functions that includes the completeness of system infrastructure and functional completeness; (342) Determination of key impact chain system weaknesses: Determine the key impact chain and system weaknesses based on the functional interactions and impact paths between the system layers in the system function multi-layer model.

2. The dynamic strike plan decision method according to claim 1 is characterized in that: The steps for establishing the weapon strike damage effect database (20) include: (21) Damage effect data collection: Collection of weapon damage effect data covering a variety of weapon types and damage modes, including experimental data, historical accident data, and computer simulation data; (22) Protection technology data collection: Collect protection technology data from test data, historical data, and simulation data; (23) Database establishment: Pre-process, classify and integrate the damage effect data and protection technology data, enter them into the database system, and establish a database on the damage effects of weapon strikes.

3. The dynamic strike plan decision method according to claim 2 is characterized in that: The (23) database establishment step comprises: (231) Data preprocessing: remove or correct outliers, standardize feature values, and normalize data; (232) Data feature classification and fusion: Use convolutional neural networks to classify and fuse data features; (233) Data entry: Data entry system to establish a database on weapon strike damage effects.

4. The dynamic strike plan decision method according to claim 1 is characterized in that: The (40) strike effectiveness calculation step includes: (41) System function damage assessment: Based on the key facility strike indicators, the integrity and functional integrity of the infrastructure are assessed, and the system function damage is assessed; (42) Strike plan cost estimation: Based on the system functional damage data, the cost of weapons and ammunition, deployment and launch costs, and logistics and support costs are estimated to determine the cost of the strike plan.

5. The dynamic attack plan decision method according to claim 1 is characterized in that: The (50) strike plan decision-making steps include: (51) Ammunition use planning: planning the explosion point and explosion method based on the type and equivalent of ammunition and the target type, distribution and protection level; (52) Selection of the optimal strike plan: Dynamically select the optimal strike plan based on the optimal cost-effectiveness of the critical infrastructure under the set strike indicators.

6. The dynamic attack plan decision method according to claim 5 is characterized in that: The (51) munitions use planning steps include: (511) Selection of ammunition type: refer to the database for the destructive power, penetration capability and effectiveness against specific targets of each type of ammunition to select the type of ammunition to be used; (512) Determine the munitions equivalent: Based on the assessment results, the munitions equivalent sufficient to achieve the desired destructive effect shall be determined taking into account the structural strength, location and protective measures of the target and the explosive equivalent required for each target; (513) Calculation of the number of ammunition required: Calculate the number of ammunition required based on the size, shape and distribution of the target; (514) Explosion point analysis and explosion mode optimization: Dynamically match the ammunition strike characteristics with the target damage characteristics, determine the ammunition explosion point based on the strike indicators and target structure damage response, and determine the best detonation method based on the target information extracted from the geographic information system, including target characteristics and the scene in which the target is located.

7. The dynamic attack plan decision method according to claim 6 is characterized in that: The (52) optimal attack plan selection step includes: (521) Identification of key infrastructure: Identify key infrastructure according to its importance in the functional model of the urban system and mark it as a key node; (522) Setting strike targets: Based on human resources, weapons, ammunition resources and strategic needs, set specific strike targets for each key facility. At the same time, based on the destruction results of key facility nodes and their chain reactions in the multi-layer model of system functions, evaluate the potential impact of the strike on the overall system. (523) Cost-effectiveness optimization: Taking the cost-effectiveness as the objective function, maximizing the strike benefit, taking the feasibility and economy of the plan as constraints, using genetic algorithms to generate multiple strike plans, and evaluating the fitness of each plan; (524) Dynamic programming and path optimization: The strike decision-making process is broken down into multiple stages. Dynamic programming decisions are made at each stage based on the current state and possible future states. The possibility and effect of state transitions at each stage are analyzed, and the benefits and risks of different decision paths are evaluated. (525) Selection of the optimal strike plan: Compare the benefits and risks of each decision path, select the path with the highest overall benefit and the lowest risk, and form the optimal strike plan.

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