DocumentCode :
2752609
Title :
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
Link To Document :
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