A hybrid design method of fuzzy systems

Ying Li; Rongchun Zhao; Yanning Zhang

A hybrid design method of fuzzy systems

Ying Li, Rongchun Zhao, Yanning Zhang

School of Computer Science

Northwestern Polytechnical University Xian

Research output: Contribution to conference › Paper › peer-review

Abstract

A hybrid approach for designing fuzzy rule-based systems based on clustering and a class of fuzzy neural networks is introduced. Firstly, an unsupervised clustering technique is used to determine the number of fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Secondly, a class of fuzzy neural networks is constructed and its weights are tuned to make the parameters of the constructed fuzzy rule base more precise. Finally, we focus on function approximation problems as a vehicle to evaluate its performance.

Original language	English
Pages	1618-1621
Number of pages	4
State	Published - 2004
Event	2004 7th International Conference on Signal Processing Proceedings (ICSP'04) - Beijing, China Duration: 31 Aug 2004 → 4 Sep 2004

Conference

Conference	2004 7th International Conference on Signal Processing Proceedings (ICSP'04)
Country/Territory	China
City	Beijing
Period	31/08/04 → 4/09/04

Keywords

Fuzzy rule base
Fuzzy systems design
Neurofuzzy networks

Cite this

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title = "A hybrid design method of fuzzy systems",

abstract = "A hybrid approach for designing fuzzy rule-based systems based on clustering and a class of fuzzy neural networks is introduced. Firstly, an unsupervised clustering technique is used to determine the number of fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Secondly, a class of fuzzy neural networks is constructed and its weights are tuned to make the parameters of the constructed fuzzy rule base more precise. Finally, we focus on function approximation problems as a vehicle to evaluate its performance.",

keywords = "Fuzzy rule base, Fuzzy systems design, Neurofuzzy networks",

author = "Ying Li and Rongchun Zhao and Yanning Zhang",

year = "2004",

language = "英语",

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note = "2004 7th International Conference on Signal Processing Proceedings (ICSP'04) ; Conference date: 31-08-2004 Through 04-09-2004",

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AU - Li, Ying

AU - Zhao, Rongchun

AU - Zhang, Yanning

PY - 2004

Y1 - 2004

N2 - A hybrid approach for designing fuzzy rule-based systems based on clustering and a class of fuzzy neural networks is introduced. Firstly, an unsupervised clustering technique is used to determine the number of fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Secondly, a class of fuzzy neural networks is constructed and its weights are tuned to make the parameters of the constructed fuzzy rule base more precise. Finally, we focus on function approximation problems as a vehicle to evaluate its performance.

AB - A hybrid approach for designing fuzzy rule-based systems based on clustering and a class of fuzzy neural networks is introduced. Firstly, an unsupervised clustering technique is used to determine the number of fuzzy rules and generate an initial fuzzy rule base from the given input-output data. Secondly, a class of fuzzy neural networks is constructed and its weights are tuned to make the parameters of the constructed fuzzy rule base more precise. Finally, we focus on function approximation problems as a vehicle to evaluate its performance.

KW - Fuzzy rule base

KW - Fuzzy systems design

KW - Neurofuzzy networks

UR - http://www.scopus.com/inward/record.url?scp=7744233476&partnerID=8YFLogxK

M3 - 论文

AN - SCOPUS:7744233476

SP - 1618

EP - 1621

T2 - 2004 7th International Conference on Signal Processing Proceedings (ICSP'04)

Y2 - 31 August 2004 through 4 September 2004

ER -

A hybrid design method of fuzzy systems

Abstract

Conference

Keywords

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