Influence of Difference among Evolutionary Computations for Design Information

• CHIBA Kazuhisa

  Hokkaido Institute of Technology

抄録

Design informatics, which is the efficient design methodology, has three points of view. The first is the efficient exploration in design space using evolutionary-based optimization methods. The second is the structuring and visualizing of design space using data mining techniques. The third is the application to practical problems. In the present study, the influence of the difference among the seven pure and hybrid optimization methods for design information has been investigated in order to explain the selection manner of optimization methods for data mining. The practical problem of a single-stage hybrid rocket is picked up as the present design object. A functional analysis of variance and a self-organizing map are employed as data mining techniques in order to acquire the global information in design space. As a result, mining result depends on not the number of generation (i.e. convergence) but the optimization methods (i.e. diversity). Consequently, the optimization method with diversity performance is the beneficial selection in order to obtain the global design information in design space.

収録刊行物

• Journal of Computational Science and Technology

  Journal of Computational Science and Technology 7 (2), 184-195, 2013

  一般社団法人 日本機械学会

キーワード

• Design Informatics
• Evolutionary Computation
• Data Mining
• Large-Scale Practical Problem.

詳細情報

• CRID: 1390001205275407104
• NII論文ID: 130003368079
• DOI: 10.1299/jcst.7.184
• ISSN: 18816894
• Web Site: https://www.jstage.jst.go.jp/article/jcst/7/2/7_184/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可