教師資料查詢 | 類別: 期刊論文 | 教師: 李宜勳 LIN, I-HSUN (瀏覽個人網頁)

標題:A Dynamic Hierarchical Fuzzy Neural Network for A General Continuous Function
學年97
學期1
出版(發表)日期2008/09/23
作品名稱A Dynamic Hierarchical Fuzzy Neural Network for A General Continuous Function
作品名稱(其他語言)
著者W. Y. Wang, I.H. Li, S.C. Li, M.S. Tsai, and S.F Su
單位
出版者
著錄名稱、卷期、頁數International Journal of Fuzzy Systems 11(2), p.130-136
摘要A serious problem limiting the applicability of the fuzzy neural networks is the "curse of dimensionality", especially for general continuous functions. A way to deal with this problem is to construct a dynamic hierarchical fuzzy neural network. In this paper, we propose a two-stage genetic algorithm to intelligently construct the dynamic hierarchical fuzzy neural network (HFNN) based on the merged-FNN for general continuous functions. First, we use a genetic algorithm which is popular for flowshop scheduling problems (GAFSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GAFSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.
關鍵字Fuzzy systems;Conferences
語言英文
ISSN1098-7584
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度
國別德國
公開徵稿
出版型式,電子版
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