Learning Technique for TSK Fuzzy Based on Cooperative

摘要：

TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. Fuzzy model is decomposed into two populations: one population describes fuzzy model and its rule construction, and the other population depicts fuzzy partition and membership function parameters. The technique presented has merits in little prior knowledge, rapid convergence and concise fuzzy model. Example of function approximation shows the techniques validity.

作者: Guohui YANG Qun WU Xiaoguang HU Yu JIANG

作者单位: Harbin Institute of Technology, China Beijing University of Aeronautics and Astronautics, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）