Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 전상운 | - |
dc.date.accessioned | 2024-04-30T00:53:35Z | - |
dc.date.available | 2024-04-30T00:53:35Z | - |
dc.date.issued | 2023-05 | - |
dc.identifier.citation | 2023 15th International Conference on Advanced Computational Intelligence (ICACI) | en_US |
dc.identifier.isbn | 979-8-3503-2145-6 | - |
dc.identifier.uri | https://information.hanyang.ac.kr/#/eds/detail?an=edseee.10146187&dbId=edseee | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/190084 | - |
dc.description.abstract | Particle Swarm Optimization (PSO) is one of the best solutions that can find the optimal solution to an optimization problem. While, the canonical PSO may suffer from the problems that it can trap in a local optima during some successive generations from the beginning to the end of the stopping criteria. To make the population of PSO escape from the local optima quickly, an Orthogonal Latin Square (OLS) based experimental design method is applied and can significantly improve the convergence performance. In this article, an OLS based PSO algorithm is proposed which can be used if the PSO algorithm traps into a local optima during the convergence time. In the iteration, the OLS based design method will be implemented to help the population escape to better positions only when the population falls into local optima. And the bestso- far position can be replaced by a better one around it. In this way, a shortened convergence time is shown compared with the canonical PSO algorithm as well as a better final best fitness value. When applying our proposed algorithm in the test functions, the result shows that our proposed algorithm can find the optimal solutions with an excellent convergence time. | en_US |
dc.description.sponsorship | This work was supported in part by the Korea Evaluation Institute Of Industrial Technology (KEIT) grant funded by the Korean government (KCG, MOIS, NFA) [RS-2022-001549812, Development of technology to respond to marine fires and chemical accidents using wearable devices], in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1F1A1071093). | en_US |
dc.language | en_US | en_US |
dc.publisher | IEEE | en_US |
dc.relation.ispartofseries | ;1-6 | - |
dc.subject | Particle swarm optimization (PSO) | en_US |
dc.subject | p Best | en_US |
dc.subject | g Best | en_US |
dc.subject | Orthogonal Latin Square (OLS) | en_US |
dc.subject | Orthogonal design scheme | en_US |
dc.title | Orthogonal latin square based particle swarm optimization: A dynamic approach for continues functions optimization | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICACI58115.2023.10146187 | en_US |
dc.relation.page | 1-6 | - |
dc.contributor.googleauthor | Gao, Zhanyang | - |
dc.contributor.googleauthor | Sun, Peifa | - |
dc.contributor.googleauthor | Li, Mingyu | - |
dc.contributor.googleauthor | Jeon, Sang-Woon | - |
dc.contributor.googleauthor | Jin, Hu | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | SCHOOL OF ELECTRICAL ENGINEERING | - |
dc.identifier.pid | sangwoonjeon | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.