Rule Reduction in Air Combat Belief Rule Base Based on Fuzzy-Rough Set
Baibing Wu, Jian Huang, Wanying Gao, Jiangtao Kong · 2016
Because of the complicated air combat situation, more condition attributes and attributes values are contained in the air combat maneuvers belief rule base (BRB). Tens of thousands of rules lead to combination explosion problem, which degrades the inference speed seriously. Based on fuzzy rough set theory, this paper introduces information entropy to measure the significance of condition attribute, and use k-prototypes to measure the similarity between attributes values. Experiments show the reduction algorithm has a great performance in rule reduction of air combat maneuvers.