Paper Info
Title
The Extension-Based Ant Colony Optimization of Finding Rough Set Reducts
Abstract
Ant colony algorithm is a simulated evolutionary algorithm, which shows many excellent characters and has succeeded in solving many difficult combinatorial optimization problems. However, it is not perfect now. Inspired by Dependent Function of Extension Theory, a new statue transition rule and local updating rule based on Dependent Function have been presented in this paper. And experimental results show that our algorithm is effective and useful.
Year
DOI
Venue
2009
10.1109/IFITA.2009.336
IFITA (3)
Keywords
Field
DocType
finding rough set reducts,excellent character,extension-based ant colony optimization,new statue transition rule,simulated evolutionary algorithm,ant colony algorithm,dependent function,difficult combinatorial optimization problem,extension theory,ant colony optimization,evolutionary computation,information technology,data mining,iterative algorithm,rough set theory,application software,computer simulation,probability density function,computational modeling
Ant colony optimization algorithms,Rule-based system,Evolutionary algorithm,Iterative method,Meta-optimization,Evolutionary computation,Algorithm,Rough set,Selection rule,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Zhao Sujuan100.34
Zeng Tao200.34
Yu Yongquan363.22