A structure learning method for concise fuzzy systems

Author

Wang, Di ; Zeng, Xiao-Jun ; Keane, John A.

Author_Institution

EBTIC, Khalifa Univ., Abu Dhabi, United Arab Emirates

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

8

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.

Keywords

fuzzy systems; learning (artificial intelligence); ECSFS; Mamdani fuzzy system; SELM; TS fuzzy system; evolving construction scheme for fuzzy systems; learning process; structure evolving learning method for fuzzy systems; Accuracy; Equations; Fuzzy systems; Indexes; Input variables; Learning systems; Noise; Mamdani Fuzzy Systems; TS fuzzy system; fuzzy systems; system identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on

Conference_Location

Brisbane, QLD

ISSN

1098-7584

Print_ISBN

978-1-4673-1507-4

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZ-IEEE.2012.6251171

Filename

6251171