Title
Recursive particle swarm optimization applications in radial basis function networks modeling system
Abstract
A novel strategy on particle swarm optimization is proposed to solve dynamic optimization problems, in which the data are obtained not once for all but one by one. The evolutionary states of the particle swarm are guided recursively by the proposed algorithm, according to the information achieved by the continuous data and the prior estimated knowledge on the solution space. The experimental results for three test functions show that radial basis function networks modeling system based on the proposed recursive algorithm requires fewer radial basis functions and gives more accurate results than other traditional improved PSO in solving dynamic problems.
Year
DOI
Venue
2011
10.1109/BMEI.2011.6098689
2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)
Keywords
Field
DocType
PSO,Recursive,Radial Basis Function Networks Modeling System
Particle swarm optimization,Radial basis function network,Mathematical optimization,Recursion (computer science),Radial basis function,Computer science,Multi-swarm optimization,Dynamic problem,Optimization problem,Recursion
Conference
Volume
Issue
ISSN
4
null
1948-2914
ISBN
Citations 
PageRank 
978-1-4244-9351-7
0
0.34
References 
Authors
2
6
Name
Order
Citations
PageRank
Baolei Li173.85
xinling shi27415.34
Jianhua Chen3329.00
Zhenzhou An410.70
Huawei Ding500.34
Xiaofeng Wang600.34