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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zuyuan Yang Huafen Yang You Yang Lihui Zhang |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Comput. Sci. & Eng., Qujing Normal Coll., Qujing, China (Huafen Yang) || Sch. of Autom. Control & Mech. Eng., Kunming Univ., Kunming, China (Zuyuan Yang) || Metall. Coll. of Logistics, Kunming Normal Coll., Kunming, China (Lihui Zhang) || Sch. of Inf. Sci. & Eng., Chongqing Normal Univ., Chongqing, China (You Yang) |
| Abstract | This paper proposes a new particle swarm optimization method that use chaotic maps for parameter adaptation. To enhance the performance of particle swarm optimization, which is an evolutionary computation technique through individual improvement plus population cooperation and competition, a modified particle swarm optimization algorithm is proposed by incorporating chaos(CPSO). Firstly, diversity measure method is introduced into PSO to efficiently balance the exploration and exploitation abilities. Secondly, chaotic searching strategy is introduced when the population is trapped into local optimum. Experiment results and comparisons with the standard PSO and GA show that the CPSO can effectively enhance the searching efficiency and greatly improve the searching quality. |
| Starting Page | 209 |
| Ending Page | 213 |
| File Size | 3894344 |
| Page Count | 5 |
| File Format | |
| ISSN | 21579563 |
| e-ISBN | 9781479951512 |
| DOI | 10.1109/ICNC.2014.6975836 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-08-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Chaos Algorithm design and analysis population diversity Sociology Educational institutions chaos maps Statistics Particle swarm optimization Optimization Convergence |
| Content Type | Text |
| Resource Type | Article |
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