ＲＢＦネットワークとＰａｒｔｉｃｌｅ　Ｓｗａｒｍ　Ｏｐｔｉｍｉｚａｔｉｏｎによる統合的最適化

• 北山 哲士

  金沢大学

• 安田 恵一郎

  首都大学東京

• 山崎 光悦

  金沢大学

書誌事項

タイトル別名

• The Integrative Optimization by RBF Network and Particle Swarm Optimization
• RBF ネットワーク ト Particle Swarm Optimization ニ ヨル トウゴウテキ サイテキカ

抄録

This paper presents a method for the integrative optimization system. Recently, many methods for global optimization have been proposed. The objective of these methods is to find a global minimum of non-convex function. However, large numbers of function evaluations are required, in general. We utilize the response surface method to approximate function space to reduce the function evaluations. The response surface method is constructed from sampling points. The RBF Network, which is one of the neural networks, is utilized to approximate the function space. Then Particle Swarm Optimization (PSO) is applied to the response surface. Proposed system consists of three parts. That is, (Part 1) Generation of the sampling points, (Part 2) Construction of response surface by RBF Network, (Part 3) Optimization by PSO. By iterating these three parts, it is expected that the approximate global minimum of non-convex function can be obtained with a few number of function evaluations. Through numerical examples, the effectiveness and validity are examined.

収録刊行物

• 電気学会論文誌Ｃ（電子・情報・システム部門誌）

  電気学会論文誌Ｃ（電子・情報・システム部門誌） 128 (4), 636-645, 2008

  一般社団法人 電気学会

キーワード

• 大域的最適化
• RBFネットワーク
• Particle Swarm Optimization
• 応答曲面

詳細情報

• CRID: 1390282679582590464
• NII論文ID: 10021132148
• NII書誌ID: AN10065950
• DOI: 10.1541/ieejeiss.128.636
• ISSN: 13488155
• ISSN: 03854221
• NDL書誌ID: 9451525
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I9451525
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/128/4/128_4_636/_pdf
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可