Rule Reduction in Air Combat Belief Rule Base Based on Fuzzy-Rough Set
| Autor: | Jian Huang, Baibing Wu, Wanying Gao, Jiangtao Kong |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Similarity (geometry)
business.industry Fuzzy set Inference ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Base (topology) computer.software_genre 01 natural sciences Measure (mathematics) Reduction (complexity) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Algorithm design Rough set Artificial intelligence Data mining 010306 general physics business computer Mathematics |
| Zdroj: | 2016 3rd International Conference on Information Science and Control Engineering (ICISCE). |
| DOI: | 10.1109/icisce.2016.132 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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