CN-122022508-A - Equipment capability assessment method based on dual assessment framework

CN122022508ACN 122022508 ACN122022508 ACN 122022508ACN-122022508-A

Abstract

The invention relates to the technical field of equipment capability assessment in a system combat background and discloses an equipment capability assessment method based on a dual assessment framework, which comprises the following steps of S1, establishing a dual assessment framework, wherein the dual assessment framework comprises a meta assessment layer, an equipment assessment layer and a meta assessment verification layer; S2, establishing a meta-evaluation index model containing at least 6 core indexes in a meta-evaluation layer, optimizing candidate evaluation methods by adopting an entropy weight method-TOPSIS combined model, S3, establishing a three-level equipment evaluation index model in an equipment evaluation layer, wherein the three-level equipment evaluation index model comprises a target layer, a criterion layer and a sub-index layer, and S4, checking the credibility of equipment evaluation results by adopting a group decision evaluation method in a meta-evaluation verification layer. The method is suitable for military equipment capability assessment and combat scheme model selection decision, can improve accuracy, stability and decision efficiency of assessment results, is highly consistent with expert consensus, and has practical application feasibility and operability.

Inventors

HUANG YANYAN
Ge Renxiang
ZHOU HUADONG
Wu Hanye

Assignees

南京理工大学

Dates

Publication Date: 20260512
Application Date: 20251125

Claims (8)

1. An equipment capability assessment method based on a dual assessment framework is characterized by comprising the following steps: s1, establishing a double evaluation framework, wherein the double evaluation framework comprises a meta evaluation layer, an equipment evaluation layer and a meta evaluation verification layer; S2, establishing a meta-evaluation index model containing at least 6 core indexes in a meta-evaluation layer, optimizing candidate evaluation methods by adopting an entropy weight method-TOPSIS combined model, and outputting an optimal evaluation method; S3, in an equipment evaluation layer, a three-level equipment evaluation index model is established, wherein the three-level equipment evaluation index model comprises a target layer, a criterion layer and a sub-index layer; and S4, in the meta-evaluation verification layer, performing reliability verification on the equipment evaluation result by adopting a group decision evaluation method, and if the reliability verification is not passed, feeding back to the meta-evaluation layer or the equipment evaluation layer for parameter adjustment to form closed-loop optimization.
2. The method for evaluating equipment capability based on a dual evaluation framework according to claim 1, wherein the meta-evaluation index model comprises 6 indexes of evaluation accuracy, result stability, process objectivity, calculation complexity, processing uncertainty capability, and result interpretability, wherein the evaluation accuracy, the result stability, and the calculation complexity are cost-type indexes, and the process objectivity, the processing uncertainty capability, and the result interpretability are benefit-type indexes.
3. The equipment capability assessment method based on the dual assessment framework according to claim 1, wherein the implementation of the entropy weight method-TOPSIS combination model in the meta assessment layer of S2 comprises the following steps: s21, constructing a meta evaluation decision matrix; S22, carrying out standardization processing on the index data; S23, calculating each index weight by adopting an entropy weight method; S24, calculating the closeness of each candidate method by adopting a TOPSIS method, and selecting the method with the highest closeness as the optimal evaluation method.
4. The equipment capability assessment method based on the dual assessment framework according to claim 1, wherein the implementation of the entropy weight-AHP combination weighting method in the equipment assessment layer of S3 comprises the following steps: S31, constructing an equipment original data matrix; s32, carrying out standardized processing on the data; s33, calculating objective weights by adopting an entropy weight method, and calculating subjective weights by adopting an AHP method; S34, fusing the objective weight and the subjective weight according to a preset coefficient to obtain the combined weight.
5. The equipment capability assessment method based on the dual assessment framework according to claim 4, wherein the calculation formula of the combining weights is: , wherein, For the weight of the entropy weight method, The weight of the method is given by the AHP method, Is a preference coefficient.
6. The equipment capability assessment method based on the dual assessment framework according to claim 1, wherein the implementation of the group decision assessment method in the meta assessment verification layer of S4 comprises the steps of: S41, the expert independently ranks the equipment schemes to form expert consensus ranks; s42, calculating a Speermann level correlation coefficient rho between the evaluation result sequence and the expert consensus sequence; S43, if ρ is more than or equal to 0.90, checking, otherwise, feeding back adjustment parameters and reevaluating.
7. The equipment capability assessment method based on the dual assessment framework according to claim 1, wherein in the three-level equipment assessment index model, a criterion layer comprises at least five capability dimensions including a hit capability, a guard capability, a maneuvering capability, a reconnaissance capability, and a communication capability, and a sub-index layer comprises quantifiable parameters in each capability dimension.
8. The equipment capability assessment method based on the dual assessment framework according to claim 1, wherein the candidate assessment method includes at least two of a fuzzy logic method, a TOPSIS method, and a utility function method.

Description

Equipment capability assessment method based on dual assessment framework Technical Field The invention relates to the technical field of equipment capability assessment in a system combat background, in particular to an equipment capability assessment method based on a dual assessment framework. Background In modern military combat, equipment capability assessment is a core link of combat scheme iterative optimization and equipment selection decision, and system combat scheme decision requires stable and reliable equipment combat capability assessment result support. For this reason, to obtain an excellent equipment ability evaluation method, the evaluation method needs to be evaluated, so this study is called double evaluation. The method needs cascade evaluation, an evaluation framework is uniformly constructed, and an optimal evaluation method obtained by evaluation is used as a reliable evaluation method for equipment capability evaluation. In order to effectively cope with the above challenges, there is a need for an equipment capability assessment method that can implement objective optimization of the assessment method, quantitative equipment capability assessment, and closed-loop verification of result reliability, so as to solve the drawbacks of the prior art and improve the scientificity of equipment assessment and the support capability of combat decision. At present, optimization algorithms such as an entropy weight method and a TOPSIS method are preliminarily applied in the field of equipment evaluation, wherein the entropy weight method can realize objective weighting based on the degree of data variation, the TOPSIS method can realize multi-scheme optimization through double-reference distance measurement, and the AHP method can be fused with expert experience to reflect tactical requirements. However, the three are not combined with the element evaluation theory to form a closed-loop framework in the prior art, so that the objectivity, the accuracy and the credibility of the evaluation are difficult to be considered. The equipment capability assessment method based on the dual assessment framework combines the meta assessment concept to construct a dual assessment framework and an assessment flow of a meta assessment layer-equipment assessment layer. The equipment assessment layer determines the assessment index weight of each capability of the equipment through an entropy weight-AHP method, and then the assessment method determined by the meta assessment layer is adopted to complete the assessment quantification of the capability of the equipment, so that the accuracy and the stability of an assessment result are effectively improved. Disclosure of Invention Aiming at the defects in the prior art, the equipment capability assessment method based on the dual assessment framework provided by the invention realizes scientific assessment of equipment capability by constructing a closed-loop assessment framework, optimizing algorithm combinations and defining constraint conditions. In order to achieve the aim of the invention, the technical scheme adopted by the invention is that the equipment capability assessment method based on the double assessment framework comprises the following steps: s1, establishing a double evaluation framework, wherein the double evaluation framework comprises a meta evaluation layer, an equipment evaluation layer and a meta evaluation verification layer; S2, establishing a meta-evaluation index model containing at least 6 core indexes in a meta-evaluation layer, optimizing candidate evaluation methods by adopting an entropy weight method-TOPSIS combined model, and outputting an optimal evaluation method; S3, in the equipment evaluation layer, a three-level equipment evaluation index model is established, wherein the three-level equipment evaluation index model comprises a target layer, a criterion layer and a sub-index layer; and S4, in the meta-evaluation verification layer, performing reliability verification on the equipment evaluation result by adopting a group decision evaluation method, and if the reliability verification is not passed, feeding back to the meta-evaluation layer or the equipment evaluation layer for parameter adjustment to form closed-loop optimization. Further, the equipment capability assessment method based on the dual assessment framework comprises the following 6 indexes of assessment accuracy, result stability, process objectivity, calculation complexity, processing uncertainty capability and result interpretability, wherein the assessment accuracy, the result stability and the calculation complexity are cost type indexes, and the process objectivity, the processing uncertainty capability and the result interpretability are benefit type indexes. Further, the implementation of the S2 entropy weight method-TOPSIS combined model in the meta-evaluation layer of the equipment capability evaluation method based on the dual evaluation framework