A dynamic hierarchical fuzzy neural network for a general continuous function

Wei Yen Wang, I. Hsun Li, Shu Chang Li, Men Shen Tsai, Shun Feng Su

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

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 (GA_FSP) to construct the HFNN. Then, a reduced-form genetic algorithm (RGA) optimizes the HFNN constructed by GA_FSP. For a real-world application, the presented method is used to approximate the Taiwanese stock market.

原文英語
主出版物標題2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
頁面1318-1324
頁數7
DOIs
出版狀態已發佈 - 2008 十一月 7
事件2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 - Hong Kong, 中国
持續時間: 2008 六月 12008 六月 6

出版系列

名字IEEE International Conference on Fuzzy Systems
ISSN(列印)1098-7584

其他

其他2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008
國家中国
城市Hong Kong
期間08/6/108/6/6

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • 引用此

    Wang, W. Y., Li, I. H., Li, S. C., Tsai, M. S., & Su, S. F. (2008). A dynamic hierarchical fuzzy neural network for a general continuous function. 於 2008 IEEE International Conference on Fuzzy Systems, FUZZ 2008 (頁 1318-1324). [4630543] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2008.4630543