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A new simplified swarm optimization (SSO) using exchange local search scheme

Bae, Changseok and Yeh, Wei-Chang and Wahid, Noorhaniza and Chung, Yuk Ying and Liu, Yao (2012) A new simplified swarm optimization (SSO) using exchange local search scheme. International Journal of Innovative Computing, Information and Control, 8 (6). pp. 4391-4406. ISSN 13494198

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Swarm-based optimization algorithms have demonstrated to have effective ability to solve the classification problem in multiclass databases. However, these algo- rithms tend to suffer from premature convergence in the high dimensional problem space. This paper proposes a novel simplified swarm optimization (SSO) algorithm to overcome the above convergence problem by incorporating it with the new local search strategy. The proposed algorithm can find a better solution from the neighbourhood of the current solu- tion produced by SSO. The performance of the proposed algorithm has been evaluated by using 13 different widely used databases and compared with the standard PSO and three other well-known classification algorithms. In addition, the practicability of the approach is studied by applying it in analysing golf swing from weight shift data. Empirical results illustrate that the proposed algorithm can achieve the highest classification accuracy.

Item Type: Article
Uncontrolled Keywords: Particle swarm optimization; discrete particle swarm optimization; simplified swarm optimization; local search; data classification; data mining
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Multimedia
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:21
Last Modified: 13 Aug 2018 03:21
URI: http://eprints.uthm.edu.my/id/eprint/9622
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