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A new Simplified Swarm Optimization(SSO) using exchange local search scheme

A new Simplified Swarm Optimization(SSO) using exchange local search scheme
학술지명 International Journal Of Innovative Computing Information And Control ISSN 1349-4198
SCI 유무 SCI(E) 게재연월 2012-06 Vol. 8 No. 6
표준화된 순위정보영향력지수 2.93 IF - Citation -

A new Simplified Swarm Optimization(SSO) using exchange local search scheme
국제공동연구 University of Technology Sydney(Australia), University Tun Hussein Onn Malaysia(Malaysia), University of Sydney(Australia)
저자 ChangSeok Bae, WeiChang Yeh, Noorhaniza Wahid, YukYing Chung, Yao Liu
초록
Swarm-based optimization algorithms have demonstrated to have effective ability to solve the classification problem in multiclass databases. However, these algorithms 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 solution 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. 
keyword Particle swarm optimization, Discrete particle swarm optimization, Simplified swarm optimization, Local search, Data classification, Data mining

A new Simplified Swarm Optimization(SSO) using exchange local search scheme
과제명 인간 교감 신개념 UI 기반 인터랙션 기술
연구기관 한국전자통신연구원 연구책임자 손승원