A structure learning method for concise fuzzy systems

Di Wang; Xiao Jun Zeng; John A. Keane

doi:10.1109/FUZZ-IEEE.2012.6251171

A structure learning method for concise fuzzy systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a structure learning method for fuzzy systems following our previous work on a Structure Evolving Learning Method for Fuzzy Systems (SELM) and an Evolving Construction Scheme for Fuzzy Systems (ECSFS). Here we extend our previous work to a structure learning method for fuzzy systems which results in more concise systems. We analyse and compare the proposed concise structure learning strategies in terms of three aspects: (1) how to detect the splitting points for the structure learning process; (2) how to set a starting point for the fuzzy system; (3) how the proposed method is applied to Mamdani and TS fuzzy systems. © 2012 IEEE.

Original language	English
Title of host publication	IEEE International Conference on Fuzzy Systems\|IEEE Int Conf Fuzzy Syst
Publisher	IEEE
ISBN (Print)	9781467315067
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2012.6251171
Publication status	Published - 2012
Event	2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 - Brisbane, QLD Duration: 1 Jul 2012 → …

Conference

Conference	2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012
City	Brisbane, QLD
Period	1/07/12 → …

Keywords

fuzzy systems
Mamdani Fuzzy Systems
system identification
TS fuzzy system

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10.1109/FUZZ-IEEE.2012.6251171

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title = "A structure learning method for concise fuzzy systems",

abstract = "This paper presents a structure learning method for fuzzy systems following our previous work on a Structure Evolving Learning Method for Fuzzy Systems (SELM) and an Evolving Construction Scheme for Fuzzy Systems (ECSFS). Here we extend our previous work to a structure learning method for fuzzy systems which results in more concise systems. We analyse and compare the proposed concise structure learning strategies in terms of three aspects: (1) how to detect the splitting points for the structure learning process; (2) how to set a starting point for the fuzzy system; (3) how the proposed method is applied to Mamdani and TS fuzzy systems. {\textcopyright} 2012 IEEE.",

keywords = "fuzzy systems, Mamdani Fuzzy Systems, system identification, TS fuzzy system",

author = "Di Wang and Zeng, {Xiao Jun} and Keane, {John A.}",

year = "2012",

doi = "10.1109/FUZZ-IEEE.2012.6251171",

language = "English",

isbn = "9781467315067",

booktitle = "IEEE International Conference on Fuzzy Systems|IEEE Int Conf Fuzzy Syst",

publisher = "IEEE",

address = "United States",

note = "2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012 ; Conference date: 01-07-2012",

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T1 - A structure learning method for concise fuzzy systems

AU - Wang, Di

AU - Zeng, Xiao Jun

AU - Keane, John A.

PY - 2012

Y1 - 2012

N2 - This paper presents a structure learning method for fuzzy systems following our previous work on a Structure Evolving Learning Method for Fuzzy Systems (SELM) and an Evolving Construction Scheme for Fuzzy Systems (ECSFS). Here we extend our previous work to a structure learning method for fuzzy systems which results in more concise systems. We analyse and compare the proposed concise structure learning strategies in terms of three aspects: (1) how to detect the splitting points for the structure learning process; (2) how to set a starting point for the fuzzy system; (3) how the proposed method is applied to Mamdani and TS fuzzy systems. © 2012 IEEE.

AB - This paper presents a structure learning method for fuzzy systems following our previous work on a Structure Evolving Learning Method for Fuzzy Systems (SELM) and an Evolving Construction Scheme for Fuzzy Systems (ECSFS). Here we extend our previous work to a structure learning method for fuzzy systems which results in more concise systems. We analyse and compare the proposed concise structure learning strategies in terms of three aspects: (1) how to detect the splitting points for the structure learning process; (2) how to set a starting point for the fuzzy system; (3) how the proposed method is applied to Mamdani and TS fuzzy systems. © 2012 IEEE.

KW - fuzzy systems

KW - Mamdani Fuzzy Systems

KW - system identification

KW - TS fuzzy system

U2 - 10.1109/FUZZ-IEEE.2012.6251171

DO - 10.1109/FUZZ-IEEE.2012.6251171

M3 - Conference contribution

SN - 9781467315067

BT - IEEE International Conference on Fuzzy Systems|IEEE Int Conf Fuzzy Syst

PB - IEEE

T2 - 2012 IEEE International Conference on Fuzzy Systems, FUZZ 2012

Y2 - 1 July 2012

ER -

A structure learning method for concise fuzzy systems

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