DocumentCode
3318409
Title
Rough set attribute reduction algorithm based on immune genetic algorithm
Author
Zhi Jun ; Liu Jian-Yong ; Wang Zhen
Author_Institution
Zhenjiang Watercraft Coll., Zhenjiang, China
fYear
2009
fDate
8-11 Aug. 2009
Firstpage
421
Lastpage
424
Abstract
In this paper, we propose a kind of rough set attribute reduction algorithm which is based on immune genetic algorithm. It adopts adaptive crossover and mutation operators, uses the step by step evolution tactics based on shrinking precision as the stop criterion. The experiment proves that the algorithm is effective, it has improved the global search ability to avoid falling into local optimum, and it can quickly get relative minimum attribute reduction.
Keywords
genetic algorithms; rough set theory; adaptive crossover; global search ability; immune genetic algorithm; mutation operators; relative minimum attribute reduction; rough set attribute reduction algorithm; shrinking precision; step by step evolution tactics; Appraisal; Biological cells; Educational institutions; Genetic algorithms; Genetic mutations; Information systems; Production; Programmable logic arrays; Set theory; attribute reduction; immune genetic algorithm; rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-4519-6
Electronic_ISBN
978-1-4244-4520-2
Type
conf
DOI
10.1109/ICCSIT.2009.5234915
Filename
5234915
Link To Document