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標題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

語言英文

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

國別美國

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

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