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【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE
https://ptu.repo.nii.ac.jp/records/48
https://ptu.repo.nii.ac.jp/records/48bc7e5bca-30f1-4528-83c1-6b3a8f229bfc
名前 / ファイル | ライセンス | アクション |
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【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE (757.5 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2020-01-10 | |||||
タイトル | ||||||
言語 | ja | |||||
タイトル | 【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Optimization of PSO by Determining Parameters for Multiple Stages with DoE | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Metaheuristics | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | PSO | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Search performance | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Parameter tuning | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | DoE | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Metaheuristics | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | PSO | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Search performance | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | Parameter tuning | |||||
キーワード | ||||||
言語 | en | |||||
主題Scheme | Other | |||||
主題 | DoE | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
印南 , 信男
× 印南 , 信男× Innami, Michio |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Particle Swarm Optimization (PSO) is one of the population based metaheuristics. The algorithm is simple yet the convergence is rather fast. The parameter values have a large influence on the search performance. Many studies on PSO parameter tuning have been conducted so far. This paper proposes determining parameters separately in eac h stage into which the iterative process is divided, using Design of Experiments (DoE) methodology. The situation of the swarm is considered to be changing as the process proceeds. Hence, a certain effect is expected with this method. The exploration with the proposed method is performed on four test functions. Additionally the exploration with three other methods is also conducted for comparison. The proposed method yields good results. This study also reveals that the search performance improves when para meters, such as inertia weight, increase as the process proceeds. |
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書誌情報 |
技能科学研究 巻 35, 号 1, p. 36-42, 発行日 2019 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2434-3706 |