年次大会
Online ISSN : 2424-2667
ISSN-L : 2424-2667
セッションID: F011002
会議情報
F011002 機械学習を用いた最適設計
北山 哲士
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会議録・要旨集 フリー

詳細
抄録
We assume that the objectives and constraints are not explicitly known but can be evaluated through computationally intensive numerical simulation.Under this assumption,the response surface methodology(RSM) is an attractive approach.In particular,a sequential approximate optimization(SAO) is widely studied.In this paper,we investigate some characteristics of several SAO approaches.Also,future directions of SAO will be described.
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© 2012 一般社団法人 日本機械学会
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