DP鋼の応力−ひずみ曲線を支配する組織因子のスパース学習

弘川 奨悟; 田口 茂樹; 松下 康弘; 足立 吉隆

doi:10.2355/tetsutohagane.TETSU-2017-003

論文

DP鋼の応力−ひずみ曲線を支配する組織因子のスパース学習

著者情報

キーワード: sensitive analysis, data transformation, variable selection, genetic algorism, bayesian inference, sparse modelling, descriptor screening, materials genome, DP steel, stress-strain curve

ジャーナルオープンアクセス HTML

2017 年 103 巻 8 号 p. 468-474

DOI https://doi.org/10.2355/tetsutohagane.TETSU-2017-003

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詳細

抄録

Screening important microstructure factors dominantly controlling a stress-strain curve of a dual phase steel was studied by three kinds of sparse modelling approach; Sensitive analysis, data transformation & variable selection, and Bayesian inference. In addition, an effect of data noise on descriptor screening in sparse modelling was also investigated.

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