DocumentCode
724046
Title
Rough set knowledge reduction algorithm based on chaos genetic algorithm
Author
Pan Wei ; Zhu Wenliang ; Liu Sili
Author_Institution
Electr. Detection Dept., Shenyang Artillery Acad., Shenyang, China
fYear
2015
fDate
23-25 May 2015
Firstpage
1382
Lastpage
1387
Abstract
In order to obtain a valid property smallest relative reduction, this article proposed a sort of rough set knowledge reduction algorithm based on chaos genetic algorithm. The algorithm loads the chaotic variable in population genetic algorithm, making minor disturbances to progeny groups with chaos variables and adjusting perturbation amplitude gradually in the searching process to make the new algorithms not only enhancing the local search capability but also maintain the characteristics of the global optimization algorithm. At last verified by one classic example, it achieved good results whether in accuracy of reduction or in average run algebra.
Keywords
chaos; genetic algorithms; perturbation techniques; rough set theory; average run algebra; chaos genetic algorithm; global optimization algorithm; local search capability; perturbation amplitude; rough set knowledge reduction algorithm; Algebra; Chaos; Genetic algorithms; Genetics; Optimization; Sociology; Statistics; chaos genetic algorithm; crossover probability; knowledge reduction; mutation probability; rough set;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162134
Filename
7162134
Link To Document