Task association influence analysis method based on MOE and MOP

Abstract

The invention discloses a task association influence analysis method based on MOE and MOP, and the method comprises the steps: constructing an intention decomposition tree, decomposing an evaluation index, calculating the achievement degree of a corresponding combat effect and the completion degree of a tactical task through employing the MOE and the MOP, combing an association influence time sequence, evaluating the impact of the combat effect and the impact of the tactical task, and constructing an association influence value network. And calculating a total influence value of the nodes, and then analyzing and screening key tactical tasks which have important influences on battle actions through an associated influence value network. Compared with the prior art, the method has the advantages that the association influence value network is constructed based on the association influence sequence diagram, the combat effect influence value and the tactical task influence value, and the influence generated by the tactical task node in the whole battle action can be effectively described.

Description

Technical Field

[0001] The present invention belongs to the technical field of mission - related impact analysis, and particularly relates to a mission - related impact analysis method based on MOE and MOP. Background Art

[0002] A battle operation often involves multiple tactical missions, and there are complex relationships among these missions. When the battle situation develops in a direction deviating from the commander's expectation, how to find the key missions with the largest influence range and the most important role from a large number of tactical missions becomes an urgent problem.

[0003] Effectiveness index evaluation and performance index evaluation are important contents of combat evaluation. The effectiveness index (Measure of Effectiveness, MOE), also called the effectiveness index, describes the degree of change in the behavior or ability of a system, and is usually related to achieving combat objectives or producing combat effects. The performance index (Measure of Performance, MOP), also called the performance index, is used to evaluate the degree to which a force achieves the established mission objectives in the implementation of combat missions. The Chinese patent "Method for Evaluating the Management Effectiveness of the Sea Battlefield" with the application number 202110487530.3 starts from the perspective of evaluating the management effectiveness of the sea battlefield, establishes an influence model of MOP on MOE, integrates management elements into combat effectiveness indicators through the SEM (Structural equation modeling) method, and constructs an MOE - MOP - SEM model for comprehensive evaluation of the management effectiveness of the sea battlefield. This model does not evaluate the associated impacts between missions.

[0004] How to use effectiveness indicators and performance indicators to more effectively evaluate the achievement degree of combat effects and the completion degree of tactical missions, and thus provide a good data basis for subsequent mission - related impact analysis is an urgent problem to be solved. Summary of the Invention

[0005] Object of the Invention: The technical problem to be solved by the present invention is to provide a mission - related impact analysis method based on MOE and MOP in view of the deficiencies of the prior art.

[0006] To solve the above - mentioned technical problem, the present invention discloses a mission - related impact analysis method based on MOE and MOP, and the steps are as follows:

[0007] Step 1: Construct an intention decomposition tree. Decompose the combat intention of the battle operation into a three - level tree structure of "combat objective - combat effect - tactical mission".

[0008] Step 2, Decomposition of evaluation indicators. Decompose the combat effectiveness into several effectiveness indicators for trend analysis over time; decompose the tactical tasks into several execution indicators.

[0009] Step 3, Evaluation of combat effectiveness achievement. Based on the evaluation results of the effectiveness indicators at the stage of the battlefield, analyze the achievement of each combat effectiveness.

[0010] Step 4, Evaluation of tactical task completion. Based on the evaluation results of the execution indicators at the stage of the battlefield, analyze the completion of each tactical task.

[0011] Step 5, Sorting out the associated influence time sequence. Rearrange the associated influence relationships between tactical tasks and combat effectiveness according to the time sequence requirements and execution conditions.

[0012] Step 6, Evaluation of combat effectiveness influence. Calculate the influence value of a single combat effectiveness on tactical tasks.

[0013] Step 7, Evaluation of tactical task influence. Calculate the influence value of a single tactical task on combat effectiveness.

[0014] Step 8, Construct the associated influence value network. Construct the associated influence value network based on the associated influence time sequence diagram and the calculated influence values.

[0015] Step 9, Calculate the total influence value of nodes. Calculate the total influence value of each level of nodes based on the recursive method.

[0016] Step 10, Screening of key tactical tasks. Screen the key tactical tasks based on the total influence value of each node in the associated influence value network.

[0017] Furthermore, denote that a battle operation has N combat objectives O1, O2, …, O N , N ≥ 1. For any combat objective O i , 1 ≤ i ≤ N, decompose it into M i combat effectivenesses that describe the change degree of the enemy's system capabilities or battlefield environmental elements For any combat effectiveness E j , 1 ≤ j ≤ M i , find all L j tactical tasks that can affect or contribute to this effectiveness Thus, a three-level decomposition tree of combat objective-combat effectiveness-tactical task is formed;

[0018] Step 2 includes: For any combat effectiveness E j , decompose it into multiple effectiveness indicators for trend analysis over time For any tactical task T k , 1 ≤ k ≤ L j , decompose it into multiple execution indicators

[0019] Further, the steps for evaluating the achievement degree of combat effectiveness in step 3 are as follows:

[0020] Step 3-1, assume that the MOE of each effectiveness index r takes values in the interval (0, 1), 1 ≤ r ≤ R j , for any combat effectiveness E j , preset the influence weight α r of each effectiveness index MOE r such that the sum of the weights is exactly 1;

[0021] Step 3-2, assume that the achievement degree of combat effectiveness follows a one-sided normal distribution, and the phased evaluation result of combat effectiveness E j is then E j ∈(0, 1).

[0022] Further, the steps for evaluating the completion degree of tactical tasks in step 4 are as follows:

[0023] Step 4-1, assume that the MOP of each execution index s takes values in the interval (0, 1), 1 ≤ s ≤ S k , for any tactical task T k , preset the influence weight β s of each execution index MOP s such that the sum of the weights is exactly 1;

[0024] Step 4-2, assume that the completion degree of tactical tasks follows a one-sided normal distribution, and the phased evaluation result of tactical task T k is then T k ∈(0, 1).

[0025] Further, step 5 includes: rearranging the tactical tasks and combat effectiveness according to the timing requirements. First, find the first group of tactical tasks that occur, ensure that the combat effectiveness they produce is independent of each other, and constitutes the premise for the implementation of subsequent tactical tasks, and then repeat this operation until all tactical tasks and combat effectiveness are arranged; thus, a task-effect influence timing diagram is formed, and the influence timing diagram is a hierarchical directed acyclic graph.

[0026] Further, the steps for evaluating the impact of combat effectiveness in step 6 are as follows:

[0027] Step 6-1, define the overall combat effectiveness impact factor and calculate the impact value of the overall combat effectiveness on the tactical tasks;

[0028] Step 6-2: Calculate the impact value of a single combat effect on a tactical mission.

[0029] Furthermore, the overall combat effect impact factors defined in Step 6 include:

[0030] Assume that the value of the combat effect achievement degree after the battlefield stage assessment is Define the overall combat effect impact factor EIF k as follows:

[0031]

[0032] where λ k represents the expected overall combat effect achievement degree, represents the achievement degree of combat effect E j higher than the probability of this event occurring, and γ j is the importance level of E j .

[0033] Furthermore, the steps for tactical mission impact assessment in Step 7 are as follows:

[0034] Step 7-1: Define the overall tactical mission impact factor and calculate the impact value of the overall tactical mission on the combat effect;

[0035] Step 7-2: Calculate the impact value of a single tactical mission on the combat effect;

[0036] Among them, the defined overall tactical mission impact factors include:

[0037] Assume that the value of the tactical mission completion degree after the battlefield stage assessment is Define the overall tactical mission impact factor TIF j as follows:

[0038]

[0039] where μ j represents the expected overall tactical mission completion degree, while represents the achievement degree of tactical mission T k higher than the probability of this event occurring, and δ k is the importance level of T k .

[0040] Furthermore, Step 8 includes: Based on the task-effect impact time sequence diagram, for each task node T k , take the product of the corresponding tactical mission completion degree and the importance of this tactical mission as the node value; for each effect node E j, take the product of the corresponding combat effect achievement degree and the importance of this combat effect as the node value; for each directed edge starting from the tactical task T k to the combat effect E j , take the influence value of a single tactical task T k on the combat effect E j as the edge value; for each directed edge starting from the combat effect E j to the tactical task T k , take the influence value of a single combat effect E j on the tactical task T k as the edge value; in this way, a task - effect influence value network is formed, and the influence value network is a weighted hierarchical directed acyclic graph.

[0041] Furthermore, the steps for calculating the total influence value of nodes in step 9 are as follows:

[0042] Use a recursive method to calculate the total influence value of each node in the associated influence value network layer by layer. For any node V, assume its out - degree is H, and V points to nodes V1, V2, …, V H , and the corresponding edges are E1, E2, …, E H ; denote the node value of node V itself as V0 and the importance as Z0, and denote the total influence values of nodes V1, V2, …, V H as V1, V2, …, V H and the importances as Z1, Z2, …, Z H , and the edge values of edges E1, E2, …, E H as E1, E2, …, E H , then the total influence value of node V is

[0043]

[0044] Thus, calculate the total influence value of each node in the entire task - effect influence value network.

[0045] Beneficial effects: The present application provides a method for analyzing the associated impacts of several tactical tasks to find the key task with the greatest influence when the battlefield situation deviates from expectations. Compared with the prior art, the present invention has the following remarkable advantages: (1) MOE and MOP are used for combat assessment, and the results are more objective and accurate than traditional assessment methods. Therefore, based on MOE, the achievement degree of combat effects is analyzed, and based on MOP, the completion degree of tactical tasks can better reflect the combat effects and the realization of tactical tasks; (2) By constructing the combat effect impact value and the tactical task impact value, the impact of combat effects on tactical tasks and vice versa can be relatively accurately evaluated; (3) Based on the associated impact time series diagram, combat effect impact value, and tactical task impact value, an associated impact value network is constructed, which can effectively depict the influence generated by tactical task nodes in the entire campaign operation. Brief Description of the Drawings

[0046] The following further specific descriptions of the present invention will be given in conjunction with the drawings and specific embodiments, and the above and / or other advantages of the present invention will become clearer.

[0047] Figure 1 is the algorithm flowchart of task associated impact analysis.

[0048] Figure 2 is the schematic diagram of "objective-effect-task" decomposition.

[0049] Figure 3 is the "task-effect" associated impact time series diagram.

[0050] Figure 4 is the "task-effect" associated impact value network. Specific Embodiments

[0051] The embodiments of the present invention will be described below in conjunction with the drawings.

[0052] The present invention is a method for task associated impact analysis based on MOE and MOP, as Figure 1 shown, and its specific implementation steps are as follows:

[0053] The first step is to construct an intention decomposition tree. First, assume that there are N combat objectives O1, O2,..., O N to be achieved in a campaign operation, where N ≥ 1. For any combat objective O i , 1 ≤ i ≤ N, it is decomposed into M i combat effects that describe the degree of change in the enemy's system capabilities or battlefield environmental elements For any combat effect E j , find all L jA tactical mission This constitutes a three - level decomposition tree of "operational objective - operational effect - tactical mission", as Figure 2 shown.

[0054] Second step, evaluation index decomposition. For any operational effect E j , 1 ≤ j ≤ M i , decompose it into several effect indicators for trend analysis over time For any tactical mission T k , 1 ≤ k ≤ L j , decompose it into several execution indicators

[0055] Third step, evaluation of the achievement degree of operational effect. Based on the evaluation results of the effect indicators at the battlefield stage, analyze the achievement of each operational effect. Here, it is assumed that the MOE r value of each effect indicator falls within the interval (0, 1), 1 ≤ r ≤ R j . For any operational effect E j , preset the influence weight α r of each effect indicator MOE r such that the sum of the weights is exactly 1. Then obtain the stage evaluation result of the operational effect E j :

[0056]

[0057] Then it can be known that E j ∈(0, 1). Assume that E j all follow a one - sided normal distribution, that is, the sample space of E j falls on (-∞, 1) (so the value of the probability density function on (-∞, 1) is doubled). Assume that the variance of the normal distribution followed by E j is taken to be small enough so that the value of E j almost all falls within (0, 1).

[0058] Fourth step, evaluation of the completion degree of tactical mission. Based on the evaluation results of the execution indicators at the battlefield stage, analyze the completion of each tactical mission. Here, it is assumed that the MOP s value of each execution indicator falls within the interval (0, 1), 1 ≤ s ≤ S k . For any tactical mission T k , preset the influence weight β s of each execution indicator MOP s such that the sum of the weights is exactly 1. Then obtain the stage evaluation result of the tactical mission T k :

[0059]

[0060] Then it can be known that T k ∈(0,1). Assume that T k all follow the unilateral normal distribution, that is, T k has a sample space falling on (-∞, 1) (so the value of the probability density function on (-∞, 1) is doubled). Assume that the variance of the normal distribution followed by T k is taken to be small enough so that the values of T k almost all fall on (0, 1).

[0061] Step 5, Sort out the associated influence time sequence. That is, rearrange the tactical tasks and combat effects according to the time sequence requirements. First, find the first group of tactical tasks, ensure that the combat effects they produce are independent of each other, and form the premise for the implementation of subsequent tactical tasks. Then repeat this operation until all tactical tasks and combat effects are arranged. At this point, a "task - effect" influence time sequence diagram is formed, which is a hierarchical directed acyclic graph, as Figure 3 shown.

[0062] Step 6, Evaluate the influence of combat effects. For a certain tactical task T k , assume that it is affected by the previous combat effect E j (where M k represents the total number of previous combat effects that can affect the tactical task T k ), and the corresponding importance level is γ j (a positive integer between 1 and 5 according to the importance). Assume that the value of the combat effect achievement degree after the battlefield stage assessment is Define the overall combat effect influence factor EIF k as follows:

[0063]

[0064] Among them, λ k represents the expected overall combat effect achievement degree, represents the probability that the achievement degree of the combat effect E j is higher than this event occurs.

[0065] Assume that the completion degree of the tactical task T k follows the unilateral normal distribution N(1, σ), then the variance of the normal distribution after being affected by the combat effect can be defined as :

[0066]

[0067] Then the combat effectiveness can be calculated for the overall tactical mission T k Effect Influence Value (EIV) k as follows:

[0068]

[0069] where represents the value of the completion degree of the tactical mission after the battlefield stage assessment, represents the probability that the completion degree of the tactical mission T k is higher than this event occurs under the unilateral normal distribution N(1,σ), represents the unilateral normal distribution under which the probability that the completion degree of the tactical mission T k is higher than this event occurs. EIV k characterizes the degree to which the probability that the completion degree of the tactical mission T is higher than this event occurs is affected under the condition that the combat effectiveness k takes the value of this event.

[0070] Let be an effect disturbance coefficient with a value relatively close to 0 (usually taken in the range of (0, 0.2)). Then for a single combat effectiveness E j , the single combat effectiveness influence factor EIF j of E k can be calculated similarly as follows:

[0071]

[0072] Define the variance j of the normal distribution of the tactical mission T k after a disturbance occurs to a single combat effectiveness E as:

[0073]

[0074] Then the Effect Influence Value (EIV) j of the combat effectiveness on the tactical mission T k after a disturbance occurs to a single combat effectiveness E k,j can be calculated as follows:

[0075]

[0076] Then EIV k,j - EIV k can be regarded as a single combat effectiveness Ej Impact value on tactical mission T k .

[0077] Step 7, Tactical mission impact assessment. For a certain combat effect E j , assume it is affected by the previous tactical mission , and the corresponding importance level is (a positive integer between 1 and 5 according to the importance). Assume that the value of the completion degree of the tactical mission after the battlefield stage assessment is Define the overall tactical mission impact factor TIF j as follows:

[0078]

[0079] where μ j represents the expected overall completion degree of the tactical mission, while represents the probability that the achievement degree of tactical mission T k is higher than this event occurs.

[0080] Assume that the achievement degree of combat effect E j follows a one-sided normal distribution N(1, τ), then the variance of the normal distribution affected by the tactical mission can be defined as:

[0081]

[0082] Then the impact value TIV of the overall tactical mission on combat effect E j can be calculated as follows: j where,

[0083]

[0084] represents the probability that the achievement degree of combat effect E is higher than j this event occurs under the one-sided normal distribution N(1, τ), , represents the probability that the achievement degree of combat effect E is higher than j this event occurs under the one-sided normal distribution . TIV j characterizes the degree to which the probability that the achievement degree of combat effect E is higher than is affected under the condition that the tactical mission j takes the value of this event occurs.

[0085] Let ψ ∈ (0, 1) be an effect perturbation coefficient with a value closer to 0 (generally taken on (0, 0.2)). Then for a single tactical task T k , the single tactical task impact factor TIF k of T j,k can be calculated similarly as follows:

[0086]

[0087] Define the variance of the normal distribution k of the combat effect E j after a perturbation occurs in a single tactical task T as:

[0088]

[0089] Then, after a perturbation occurs in a single tactical task T k , the influence value TIV of the tactical task j on the combat effect E j,k can be calculated as follows:

[0090]

[0091] Then TIV j,k - TIV j can be regarded as the influence value of the single tactical task T k on the combat effect E j .

[0092] Step 8: Construct the associated influence value network. Based on the obtained "task - effect" influence time - series diagram above, for each task node T k , take the product of the corresponding tactical task completion degree and the importance Z k of this tactical task as its initial node value; for each effect node E j , take the product of the corresponding combat effect achievement degree and the importance of this combat effect as its node value; for each directed edge starting from the tactical task T k to the combat effect E j , take TIV j,k - TIV j as the edge value; for each directed edge starting from the combat effect E j to the tactical task T k , take EIV k,j - EIV k as the edge value.

[0093] In this way, a "task-effect" impact value network is formed, which is a weighted hierarchical directed acyclic graph, as Figure 4 shown.

[0094] Step 9: Calculate the total impact value of nodes. First, the total impact value of each combat effect node at the bottom layer is the product of the achievement degree of each combat effect and the importance of the combat effect. Then, starting from the combat effects at the bottom layer, recursively calculate the total impact values of the upper-level tactical tasks and combat effects. For any one node V, let its out-degree be H, where H is obtained according to the impact value network, and V points to nodes V1, V2, …, V H , and the corresponding edges are E1, E2, …, E H . Denote the node value of node V itself as V0 and the importance as Z0, and denote the total impact values of nodes V1, V2, …, V H as V1, V2, …, V H and the importances as Z1, Z2, …, Z H , and the edge values of edges E1, E2, …, E H as E1, E2, …, E H . Then the total impact value of node V is

[0095]

[0096] Thus, the total impact values of all nodes in the entire "task-effect" impact value network are calculated.

[0097] Step 10: Screen key tactical tasks. Sort each tactical task according to the total impact value of each tactical task node, and then screen out the required number of key tactical tasks.

[0098] In specific implementation, the present application provides a computer storage medium and a corresponding data processing unit. Among them, the computer storage medium can store a computer program, and when the computer program is executed by the data processing unit, it can run the invention content of a task association impact analysis method based on MOE and MOP provided by the present invention and some or all of the steps in each embodiment. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), etc.

[0099] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the present invention can be implemented by means of a computer program and its corresponding general hardware platform. Based on such an understanding, the technical solutions in the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a computer program, that is, a software product. The computer program software product can be stored in a storage medium, including several instructions to enable a device including a data processing unit (which can be a personal computer, a server, a single-chip microcomputer, a MUU or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0100] The present invention provides a method for analyzing the impact of task association based on MOE and MOP. There are many methods and ways to specifically implement this technical solution. The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented by the prior art.

Claims

1. A task association impact analysis method based on MOE and MOP, characterized in that, It includes the following steps: Step 1: Construct an intention decomposition tree, and decompose the combat intention of a battle operation into a three-level tree structure of combat purpose - combat effect - tactical task; Step 2: Decompose evaluation indicators. Decompose combat effects into multiple effect indicators for trend analysis over time; decompose tactical tasks into multiple execution indicators; Step 3: Evaluate the achievement degree of combat effects. Based on the evaluation results of the effect indicators at the stage of the battlefield, analyze the achievement of each combat effect; Step 4: Evaluate the completion degree of tactical tasks. Based on the evaluation results of the execution indicators at the stage of the battlefield, analyze the completion of each tactical task; Step 5: Sort out the associated influence time sequence. Rearrange the associated influence relationship between tactical tasks and combat effects according to the time sequence requirements and execution conditions; Step 6: Evaluate the influence of combat effects. Calculate the influence value of a single combat effect on a tactical task; Step 7: Evaluate the influence of tactical tasks. Calculate the influence value of a single tactical task on a combat effect; Step 8: Construct an associated influence value network. Construct an associated influence value network based on the associated influence time sequence diagram and the calculated influence values; Step 9: Calculate the total influence value of nodes. Calculate the total influence value of each level of nodes based on a recursive method; Step 10: Screen key tactical tasks. Screen key tactical tasks based on the total influence value of each node in the associated influence value network.

2. The task association impact analysis method based on MOE and MOP according to claim 1, wherein Step 1 includes: Denote that a battle operation has N combat objectives O1, O2, …, ON to be achieved, N ≥ 1. For any combat objective Oi, 1 ≤ i ≤ N, decompose it into M combat effects that describe the degree of change in the enemy's system capabilities or battlefield environmental elements. N For any combat objective Oi, i 1 ≤ i ≤ N, decompose it into M combat effects that describe the degree of change in the enemy's system capabilities or battlefield environmental elements. i combat effects For any combat effect Ej, j 1 ≤ j ≤ M, i find all L tactical tasks that can affect or contribute to this effect. j tactical tasks Thus, a three - level decomposition tree of combat objective - combat effect - tactical task is formed. Step 2 includes: For any combat effect E j , decompose it into multiple effect indicators for trend analysis over time For any tactical mission T k , where 1 ≤ k ≤ L j , decompose it into multiple execution indicators 3. The task correlation impact analysis method based on MOE and MOP according to claim 2, wherein The steps for evaluating the achievement degree of combat effects in Step 3 are as follows: Step 3-1, assume the MOE of each effectiveness index r The value falls within the interval (0, 1), 1 ≤ r ≤ R j , for any combat effectiveness E j , preset the influence weight α r of each effectiveness index MOE t such that the sum of the weights is exactly 1; Step 3-2, assuming that the achievement degree of combat effectiveness follows a one-sided normal distribution, and the phased evaluation result of combat effectiveness E j is then E j ∈(0,1).

4. A method for analyzing the influence of task association based on MOE and MOP according to claim 3, characterized in that, The steps for evaluating the completion degree of tactical tasks in Step 4 are as follows: Step 4-1, assume that the MOP of each execution indicator s The values ​​all fall in the interval (0,1), 1≤s≤S k , for any tactical task T k , pre-set each execution indicator MOP s The influence weight β s , so that the sum of the weights is exactly 1; Step 4-2, assuming that the completion degree of the tactical mission follows a one-sided normal distribution, and the phased evaluation result of the tactical mission T k is then T k ∈(0,1).

5. The task association impact analysis method based on MOE and MOP according to claim 4, characterized in that, Step 5 includes: Rearrange tactical tasks and combat effects according to the time sequence requirements. First, find a group of tactical tasks that occur first, ensure that the combat effects they produce are independent of each other and form the premise for the implementation of subsequent tactical tasks, and then repeat this operation until all tactical tasks and combat effects are arranged. At this point, a task - effect influence time sequence diagram is formed, and the influence time sequence diagram is a hierarchical directed acyclic graph.

6. The task correlation impact analysis method based on MOE and MOP according to claim 5, characterized in that The steps for evaluating the influence of combat effects in Step 6 are as follows: Step 6 - 1: Define the overall combat effect influence factor and calculate the influence value of the overall combat effect on a tactical task; Step 6 - 2: Calculate the influence value of a single combat effect on a tactical task.

7. The task correlation impact analysis method based on MOE and MOP according to claim 6, wherein The definition of the overall combat effect influence factor in Step 6 includes: Suppose that after the battlefield stage assessment, the value of the combat effectiveness achievement degree is Define the overall combat effectiveness impact factor EIF k as follows: Among them, λ k represents the achievement degree of the expected overall combat effect, represents the combat effect E j whose achievement degree is higher than the probability of this event occurring, and γ j is the importance level of E j .

8. A method for analyzing the influence of task association based on MOE and MOP according to claim 7, characterized in that The steps for evaluating the influence of tactical tasks in Step 7 are as follows: Step 7 - 1: Define the overall tactical task influence factor and calculate the influence value of the overall tactical task on a combat effect; Step 7 - 2: Calculate the influence value of a single tactical task on a combat effect; Among them, the definition of the overall tactical task influence factor includes: Assume that after the battlefield stage assessment, the value of the tactical mission completion degree is Define the overall tactical mission impact factor TIF j as follows: Among them, μ j represents the expected overall tactical mission completion rate, while represents that the achievement rate of tactical mission T k is higher than the probability of this event occurring, and δ k is the importance level of T k .

9. A task association impact analysis method based on MOE and MOP according to claim 8, characterized in that Step 8 includes: Based on the task-effect impact timing diagram, for each task node T therein k , take the product of the corresponding tactical task completion degree and the importance of this tactical task as the node value; for each effect node E therein j , take the product of the corresponding combat effect achievement degree and the importance of this combat effect as the node value; for each directed edge starting from the tactical task T k and leading to the combat effect E j , take the impact value of a single tactical task T k on the combat effect E j as the edge value; for each directed edge starting from the combat effect E j and leading to the tactical task T k , take the impact value of a single combat effect E j on the tactical task T k as the edge value; In this way, a task-effect impact value network is formed, and the impact value network is a weighted hierarchical directed acyclic graph.

10. A method for analyzing the influence of task association based on MOE and MOP according to claim 9, characterized in that, The steps for calculating the total influence value of nodes in Step 9 are as follows: The total influence value of each node in the associated influence value network is calculated layer by layer in a recursive manner. For any one node V among them, let its out-degree be H, and V points to nodes V1, V2, …, V H , and the corresponding edges are E1, E2, …, E H ; Denote the node value of node V itself as V0 and the importance as Z0, and just denote the total influence values of nodes V1, V2, …, V H as V1, V2, …, V H , and the importance as Z1, Z2, …, Z H , and the edge values of edges E1, E2, …, E H as E1, E2, …, E H , then the total influence value of node V is Thus, calculate the total influence value of each node in the entire task - effect influence value network.

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