A Fuzzy Classification Method Based on Quantum Genetic Algorithm and Its Application in Pattern Recognition

Author

Rigui, Zhou ; Jian, Cao

Author_Institution

Coll. of Inf. Eng., East China JiaoTong Univ., Nanchang, China

fYear

2009

fDate

28-29 Dec. 2009

Firstpage

187

Lastpage

190

Abstract

A fuzzy classification system is constructed based on quantum genetic algorithm (QGA) and fuzzy theory. Firstly, fuzzy rules are generated from numerical data for classification problems, in which number axis is fuzzy partitioned with trapezoid method. Second, it uses QGA to select significant fuzzy rules and removes unnecessary rules, so fuzzy rules reach an optimization state. Finally, the feasibility and the validity of this QGA-based approach to fuzzy classification system are verified through the pattern recognition.

Keywords

fuzzy set theory; genetic algorithms; pattern classification; fuzzy classification system; fuzzy rules; fuzzy theory; optimization state; pattern recognition; quantum genetic algorithm; trapezoid method; Fuzzy control; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Genetic algorithms; Mathematics; Partitioning algorithms; Pattern recognition; Quantum computing; Quantum mechanics; fuzzy classification; fuzzy partition; quantum genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Research Challenges in Computer Science, 2009. ICRCCS '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3927-0

Electronic_ISBN

978-1-4244-5410-5

Type

conf

DOI

10.1109/ICRCCS.2009.55

Filename

5401263