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학술지 Enhancement of Particle Swarm Optimization by Stabilizing Particle Movement
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저자
김현석, 장성주, 강태규
발행일
201312
출처
ETRI Journal, v.35 no.6, pp.1168-1171
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.13.0213.0197
협약과제
12IC1400, 쌍방향 정보 교환기반 인텔리전트 복합공간용 IT 조명 시스템 기술 개발, 강태규
초록
We propose an improvement of particle swarm optimization (PSO) based on the stabilization of particle movement (PM). PSO uses a stochastic variable to avoid an unfortunate state in which every particle quickly settles into a unanimous, unchanging direction, which leads to overshoot around the optimum position, resulting in a slow convergence. This study shows that randomly located particles may converge at a fast speed and lower overshoot by using the proportional-integralderivative approach, which is a widely used feedback control mechanism. A benchmark consisting of representative training datasets in the domains of function approximations and pattern recognitions is used to evaluate the performance of the proposed PSO. The final outcome confirms the improved performance of the PSO through facilitating the stabilization of PM. © 2013 ETRI.
키워드
Neural network, Particle swarm optimization, Proportionalintegral-derivative control
KSP 제안 키워드
Control mechanism, Derivative control, Fast speed, Feedback Control, Neural networks, Optimum position, Pattern recognition, Slow convergence, improved performance, particle movement, stochastic variable