重み付き評価型の学習機能を有するアダプティブ・メッシング手法 An Adaptive Mesh Generation With Parameterized Learning

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著者

    • 野口 聡 NOGUCHI So
    • 北海道大学大学院情報科学研究科 Graduate School of Information Science and Technology, Hokkaido University

抄録

This paper presents an adaptive mesh generation with parameterized learning. The present method does not need to perform iterative processes of field analysis in contrast with the conventional adaptive meshing methods. The present method evaluates mesh qualities for each element by means of evaluation function, which is weighted linear combination of shape and area of elements, distance from material corners and so on. The element which has the worst value of the evaluation function is divided into a few elements according to its shape, and this procedure is repeated until the prescribed number of elements is obtained. By using the simple Genetic Algorithm (sGA), the weighting coefficients are optimized through learning with example models such that the resultant mesh has the lowest numerical error.<br>The good mesh can be obtained without time-consuming computation, since the weight values for the mesh features are learned by the sGA. The present method would allow us to realize effective design and development of electromagnetic machine and devices.

収録刊行物

  • 電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society  

    電気学会論文誌. D, 産業応用部門誌 = The transactions of the Institute of Electrical Engineers of Japan. D, A publication of Industry Applications Society 127(3), 293-299, 2007-03-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10018737988
  • NII書誌ID(NCID)
    AN10012320
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    09136339
  • NDL 記事登録ID
    8732491
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-1608
  • データ提供元
    CJP書誌  NDL  J-STAGE 
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