Title :
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
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;
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
DOI :
10.1109/ICRCCS.2009.55
