Soft Computing-based Assessment Method of Contribution Rate of Small Arms and Equipment System

doi:10.3969/j.issn.1000-1093.2019.05.005

Abstract

Abstract: The assessment of contribution rate of weapon equipment system is of great significance to the system's combat capability construction, operational support, and actual combat training. A soft computing-based assessment method for the contribution rate of weapon equipment system is proposed for the high nonlinearity, uncertainty and ambiguity of weapon equipment system. The fuzzy clustering method based on genetic algorithm is used for the soft classification of the weapons in the small arms system, and a fuzzy neural network based on soft classification is constructed. The fuzzy mapping chain based on the task sub-capacity-system sub-capability-total system capacity is used to solve the contribution rate. The contribution rate in the middle makes full use of the fault tolerance and robustness of the neural network to adapt to the incompleteness of data and the subjectivity of expert's cognition. The proposed method is used to analyze the case of a small arms equipment system, the contribution rate of the lower-level indicators to the higher-level indicators in the system is assessed, and the feasibility of the method is verified. Key

Key words: smallarmsandequipment, contributionrateofsystem, softcomputing, fuzzyneuralnetwork, multi-attributeutility, fuzzyclustering

CLC Number:

E917
TJ202

YAO Tianle, HU Qiwei, QI Ziyuan, WEN Liang, TAO Fenghe. Soft Computing-based Assessment Method of Contribution Rate of Small Arms and Equipment System[J]. Acta Armamentarii, 2019, 40(5): 938-945.

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第40卷第5期
2019 年5月兵工学报ACTA
ARMAMENTARIIVol.40No.5May2019