How to determine the minimum number of rules to achieve given accuracy
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作者:
Feng, W
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Hong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
Feng, W
[1
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Wang, LX
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Hong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
Wang, LX
[1
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Zhu, HY
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Hong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
Zhu, HY
[1
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Sun, YX
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Hong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
Sun, YX
[1
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机构:
[1] Hong Kong Univ Sci & Technol, Dept Elect & Elect Engn, Hong Kong, Hong Kong, Peoples R China
Fuzzy systems have been proved to be universal approximators, yet a large number of fuzzy rules may be needed for high approximation accuracy. In this paper, we consider how to determine the minimum number of fuzzy rules required in a fuzzy system for approximation to achieve a given accuracy and how to construct this fuzzy system when there are only a limited number of input-output data pairs of the unknown system. The key point is to partition the input space nonuniformity. In particular, a tunnel algorithm is utilized for the single-input case. Numerical examples are given to demonstrate the proposed idea and algorithm.
机构:
Arizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USAArizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USA
Czygrinow, A.
Hurlbert, G.
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Virginia Commonwealth Univ, Dept Math & Appl Math, Richmond, VA 23284 USAArizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USA
Hurlbert, G.
Katona, G. Y.
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Budapest Univ Technol & Econ, Dept Comp Sci & Informat Theory, MTA ELTE Numer Anal & Large Networks Res Grp, Budapest, HungaryArizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USA
Katona, G. Y.
Papp, L. F.
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Budapest Univ Technol & Econ, Dept Comp Sci & Informat Theory, MTA ELTE Numer Anal & Large Networks Res Grp, Budapest, HungaryArizona State Univ, Sch Math & Stat Sci, Tempe, AZ 85287 USA
机构:
E China Normal Univ, Dept Math, Shanghai 200241, Peoples R ChinaE China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
Xu, Mimi
Hong, Yuan
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E China Normal Univ, Dept Math, Shanghai 200241, Peoples R ChinaE China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
Hong, Yuan
Shu, Jinlong
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E China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
E China Normal Univ, Shanghai Key Lab Trustworthy Comp, Shanghai 200062, Peoples R ChinaE China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
Shu, Jinlong
Zhai, Mingqing
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E China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
Chuzhou Univ, Dept Math, Chuzhou 239012, Anhui, Peoples R ChinaE China Normal Univ, Dept Math, Shanghai 200241, Peoples R China
机构:
Yuncheng Univ, Sch Math & Informat Technol, Yuncheng 044000, Peoples R China
Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R ChinaYuncheng Univ, Sch Math & Informat Technol, Yuncheng 044000, Peoples R China
Hu, Yarong
Huang, Qiongxiang
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Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R ChinaYuncheng Univ, Sch Math & Informat Technol, Yuncheng 044000, Peoples R China
Huang, Qiongxiang
Lou, Zhenzhen
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Univ Shanghai Sci & Technol, Coll Sci, Shanghai 200093, Peoples R ChinaYuncheng Univ, Sch Math & Informat Technol, Yuncheng 044000, Peoples R China
机构:
Beijing Technol & Business Univ, Sch Math & Stat, Beijing 00048, Peoples R ChinaBeijing Technol & Business Univ, Sch Math & Stat, Beijing 00048, Peoples R China
Tian, Yuting
Tu, Jianhua
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Beijing Technol & Business Univ, Sch Math & Stat, Beijing 00048, Peoples R ChinaBeijing Technol & Business Univ, Sch Math & Stat, Beijing 00048, Peoples R China