A Method of Selecting Fuzzy Rules for Pattern Identification Based on Multi-Precision Fuzzy Partitions

摘要：

Its important to extract an appropriate fuzzy rule set for multi-classification problems that have fuzzy variables. This paper proposes a new method to make the fuzzy partitions with multi-precision firstly, then produces multiple fuzzy rule tables, makes optimization to obtain a group of elite fuzzy rules by clone selection algorithm. The simulated experiment shows that the method has the performances of fewer fuzzy rules, higher classification correctness and better plasticity than that of single fuzzy partition.

作者: YE Qing ZHAO Yan CHAI Chang CHEN Zhong

作者单位: Changsha University of Science and Technology, 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）