Modulus genetic algorithm and its appliction to fuzzy system optimization
學年 87
學期 2
發表日期 1999-07-10
作品名稱 Modulus genetic algorithm and its appliction to fuzzy system optimization
作品名稱(其他語言) 模數遺傳演算法及其在模糊系統最佳化之應用
著者 Lin, Sinn-cheng
作品所屬單位 淡江大學資訊與圖書館學系
出版者 University of British Columbia
會議名稱 Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on
會議地點 Honolulu, United States
摘要 The conventional genetic algorithm encodes the searched parameters as binary strings. After applying the basic genetic operators such as reproduction, crossover and mutation, a decoding procedure is used to convert the binary strings to the original parameter space. As the result, such an encoding/decoding procedure leads to considerable numeric errors. This paper proposes a new algorithm called modulus genetic algorithm (MGA) that uses the modulus operation to resolve this problem. In the MGA, the encoding/decoding procedure is not necessary. It has the following advantages: 1) the evolution can be speeded up; 2) the numeric truncation error can be avoided; 3) the precision of solution can be increased. The proposed MGA is applied to resolve the key problem of fuzzy inference systems-rule acquisition. The fuzzy system with MGA as learning mechanism forms an ?ntelligent fuzzy system?? Based on the proposed approach, the fuzzy rule base can be self-extracted and optimized
關鍵字
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 19990710~19990715
通訊作者
國別 USA
公開徵稿
出版型式
出處 Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on vol.1, pp.669-674
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/39988 )

機構典藏連結