摘要
武器装备体系贡献率评估对体系作战能力建设、作战使用保障和实战化训练等具有重要意义。针对武器装备体系具有高度非线性、不确定性和模糊性等特点,提出利用软计算对武器装备体系贡献率进行评估的方法。采用基于遗传算法的模糊聚类方法对轻武器体系中的武器进行软分类,构造了基于软分类的模糊神经网络;通过任务子能力-体系子能力-体系总能力的模糊映射链求解各模糊映射中的贡献率,充分发挥神经网络的容错性和鲁棒性适应数据资料不完整性和专家认识主观性的特点。采用该评估方法对某轻武器装备体系进行了实例分析,有效评估出体系中下级指标对上级指标的体系贡献率,验证了评估方法的可行性。
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.
作者
姚天乐
胡起伟
齐子元
温亮
陶凤和
YAO Tianle;HU Qiwei;QI Ziyuan;WEN Liang;TAO Fenghe(Department of Artillery Engineering, Shijiazhuang Campus, Army Engineering University, Shijiazhuang 050003, Hebei, China;Department of Equipment Command and Management, Shijiazhuang Campus, Army Engineering University,Shijiazhuang 050003, Hebei, China)
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2019年第5期938-945,共8页
Acta Armamentarii
基金
武器装备预先研究项目(9140A27040314JB34452)
关键词
轻武器装备
体系贡献率
软计算
模糊神经网络
多属性效用
模糊聚类
small arms and equipment
contribution rate of system
soft computing
fuzzy neural network
multi-attribute utility
fuzzy clustering
