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- Yamaguchi Teruyoshi
- Tokyo Metropolitan University
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- Iwasaki Nobuhiro
- Tokyo Metropolitan University
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- Yasuda Keiichiro
- Tokyo Metropolitan University
Bibliographic Information
- Other Title
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- 自律適応型Particle Swarm Optimizationに関する基礎的検討
- ジリツ テキオウガタ Particle Swarm Optimization ニ カンスル キソテキ ケントウ
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Abstract
The Particle Swarm Optimization method is one of the most powerful optimization methods available for solving global optimization problems. However, knowledge of autonomous and adaptive strategies for tuning the parameters of the method for application to large-scale nonlinear non-convex optimization problems is as yet limited. This paper describes an autonomous and adaptive strategy for tuning the parameters of the PSO method based on some numerical analysis of the behavior of PSO. The proposed autonomous and adaptive tuning strategy is based on self-tuning of the parameters of PSO, which strategy utilize the information about the frequency of an updated global best of a swarm. The feasibility and advantages of the proposed autonomous adaptive PSO algorithm are demonstrated through some numerical simulations using two typical global optimization test problems.
Journal
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 21 (0), 154-154, 2005
Japan Society for Fuzzy Theory and Intelligent Informatics
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Keywords
Details 詳細情報について
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- CRID
- 1390001205668714368
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- NII Article ID
- 130005034956
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 024279090
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed