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- Ueno Genki
- 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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- ロバスト適応型Particle Swarm Optimization
- ロバスト適応型Particle Swarm Optimizaiton
- ロバスト テキオウガタ Particle Swarm Optimizaiton
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Abstract
It is well known that Particle Swarm Optimization (PSO), which was originally proposed by J. Kennedy et al., is a powerful algorithm for solving unconstrained and constrained global optimization problems. Appropriate adjustment of its parameters, however, requires a lot of time and labor when PSO is applied to real optimization problems. In this paper, we point out that giving diversity to the parameter of each particle enables PSO to solve various problems.And we propose an algorithm that has diversity of particles and an adaptive strategy for tuning a parameter.Some numerical simulations were carried out in order to examine the search ability of the proposed approach.
Journal
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 21 (0), 155-155, 2005
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390282680645424384
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- NII Article ID
- 130005034957
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 024279099
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed