DocumentCode
3442976
Title
A Method of Selecting Fuzzy Rules for Pattern Identification Based on Multi-Precision Fuzzy Partitions
Author
Qing, Ye ; Yan, Zhao ; Chang, Chai ; Zhong, Chen
Author_Institution
Changsha Univ. of Sci. & Technol., Changsha
fYear
2007
fDate
23-25 May 2007
Firstpage
746
Lastpage
749
Abstract
It´s important to extract an appropriate fuzzy rule set for multi-classification problems that have fuzzy variables. This paper proposes a new method to make the fuzzy partitions with multi-precision firstly, then produces multiple fuzzy rule tables, makes optimization to obtain a group of elite fuzzy rules by clone selection algorithm. The simulated experiment shows that the method has the performances of fewer fuzzy rules, higher classification correctness and better plasticity than that of single fuzzy partition.
Keywords
fuzzy set theory; pattern classification; clone selection algorithm; fuzzy rule set; multiclassification problem; multiprecision fuzzy partitions; pattern identification; Appropriate technology; Cloning; Data mining; Educational institutions; Fuzzy sets; Fuzzy systems; Humans; Input variables; Optimization methods; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-0737-8
Electronic_ISBN
978-1-4244-0737-8
Type
conf
DOI
10.1109/ICIEA.2007.4318506
Filename
4318506
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