DocumentCode :
2388262
Title :
Application of Quantum Genetic Algorithm on Finding Minimal Reduct
Author :
Lv, Y.J. ; Liu, N.X.
Author_Institution :
Guangxi Univ., Guangxi
fYear :
2007
fDate :
2-4 Nov. 2007
Firstpage :
728
Lastpage :
728
Abstract :
Quantum Genetic Algorithm (QGA) is a promising area in the field of computational intelligence nowadays. Although some genetic algorithms to find minimal reduct of attributes have been proposed, most of them have some defects. On the other hand, quantum genetic algorithm has some advantages, such as strong parallelism, rapid good search capability, and small population size. In this paper, we propose a QGA to find minimal reduct based on distinction table. The algorithm can obtain the best solution with one chromosome in a short time. It is testified by two experiments that our algorithm improves the GA from four points of view: population size, parallelism, computing time and search capability.
Keywords :
genetic algorithms; computational intelligence; minimal reduct; quantum genetic algorithm; Concurrent computing; Databases; Genetic algorithms; Information science; Information systems; Mathematics; Parallel processing; Quantum computing; Quantum entanglement; Quantum mechanics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3032-1
Type :
conf
DOI :
10.1109/GrC.2007.87
Filename :
4403196
Link To Document :
بازگشت