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
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;
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
DOI :
10.1109/ICIEA.2007.4318506
