A Construction Method of a Network-Type Index System for Air Combat System Effectiveness Evaluation Based on Association Rules Mining

Aiming at the problem that the traditional tree-type and cluster-type index systems do not fully meet the requirements of complex air combat effectiveness evaluation under the background of system combat, a method of constructing network-type index system is proposed. Firstly, through the analysis of the index hierarchies of typical complex air combat systems, the capability hierarchy indexes with network characteristics are selected as the research object. Then, FP-Growth algorithm is used to mine the association rules among indexes and compared with Apriori algorithm in the difference of run time. Then, the lift is introduced to quantitatively describe the influence relationship among the indexes and the air combat effectiveness evaluation network-type index system is constructed. The feasibility and effectiveness of the proposed method are verified by simulation.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865247
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
0.00

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A Construction Method of a Network-Type Index System for Air Combat System Effectiveness Evaluation Based on Association Rules Mining

Wenhao Bi, Shaocai Yu, Hao Chen, An Zhang et al.
Advanced Decision-Making Techniques
article

A Construction Method of a Network-Type Index System for Air Combat System Effectiveness Evaluation Based on Association Rules Mining

Wenhao Bi, Shaocai Yu, Hao Chen, An Zhang, Shuaiwei Nan
article en

Abstract

Aiming at the problem that the traditional tree-type and cluster-type index systems do not fully meet the requirements of complex air combat effectiveness evaluation under the background of system combat, a method of constructing network-type index system is proposed. Firstly, through the analysis of the index hierarchies of typical complex air combat systems, the capability hierarchy indexes with network characteristics are selected as the research object. Then, FP-Growth algorithm is used to mine the association rules among indexes and compared with Apriori algorithm in the difference of run time. Then, the lift is introduced to quantitatively describe the influence relationship among the indexes and the air combat effectiveness evaluation network-type index system is constructed. The feasibility and effectiveness of the proposed method are verified by simulation.

Northwestern Polytechnical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 57%
Advanced Decision-Making Techniques
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