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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/68581

    題名: Process optimization by soft computing and its application to a wire bonding problem
    作者: 鄭啟斌
    貢獻者: 淡江大學資訊管理學系
    日期: 2004-03-28
    上傳時間: 2011-10-23 13:17:39 (UTC+8)
    摘要: Modeling and optimization of a process with multiple outputs is discussed in this paper. A neuro-fuzzy system named MANFIS, which comprises a fuzzy inference structure and neural network learning ability, is used to model a multiple output process. Optimization of such a process is formulated as a multiple objective decision making problem, and a genetic algorithm and a numerical method are introduced, respectively, to solve this problem based on the MANFIS model. We have used these two algorithms, respectively, to solve a chemical process optimization problem, and compared their performances. A combination of these two algorithms is also suggested to improve to improve performances of both algorithms. The proposed approach is also applied to a wire-bonding problem in semiconductor manufacturing.
    關聯: International Journal of Applied Science and Engineering 2(1), pp.59-71
    DOI: 10.6703%2fIJASE.2004.2(1).59
    顯示於類別:[資訊管理學系暨研究所] 期刊論文


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