Use of fuzzy neural networks with grey relations in fuzzy rules partition optimization

Hui Chen Chang; Yau Tarng Juang

doi:10.1007/11539902_147

Use of fuzzy neural networks with grey relations in fuzzy rules partition optimization

Hui Chen Chang, Yau Tarng Juang

Department of Electrical Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

The objective of this paper is to use the back-propagation (BP) algorithm in conjunction with grey relations to find the optimal partitions of the consequent part in fuzzy neural networks (FNN). A BP algorithm with grey relational coefficient (GRC) is proposed in order to decrease the square errors of the FNN for acquiring the optimal partitions of the consequent part of fuzzy rules. From the simulation results, we find that the present method applied for fuzzy logic control of an inverted pendulum has better performance than that of the traditional BP algorithm.

Original language	English
Pages (from-to)	1172-1177
Number of pages	6
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3612
Issue number	PART III
DOIs	https://doi.org/10.1007/11539902_147
State	Published - 2005
Event	First International Conference on Natural Computation, ICNC 2005 - Changsha, China Duration: 27 Aug 2005 → 29 Aug 2005

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10.1007/11539902_147

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Use of fuzzy neural networks with grey relations in fuzzy rules partition optimization. / Chang, Hui Chen; Juang, Yau Tarng.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3612, No. PART III, 2005, p. 1172-1177.

Research output: Contribution to journal › Conference article › peer-review

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AB - The objective of this paper is to use the back-propagation (BP) algorithm in conjunction with grey relations to find the optimal partitions of the consequent part in fuzzy neural networks (FNN). A BP algorithm with grey relational coefficient (GRC) is proposed in order to decrease the square errors of the FNN for acquiring the optimal partitions of the consequent part of fuzzy rules. From the simulation results, we find that the present method applied for fuzzy logic control of an inverted pendulum has better performance than that of the traditional BP algorithm.

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T2 - First International Conference on Natural Computation, ICNC 2005

Y2 - 27 August 2005 through 29 August 2005

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Use of fuzzy neural networks with grey relations in fuzzy rules partition optimization

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