日本金属学会2022年秋期(第171回)講演大会

Presentation information

一般講演

11.Computational Science » Data Science

[G] Data Science

Wed. Sep 21, 2022 3:05 PM - 5:00 PM Rm. E (D24,2Flr. Build.D)

座長:北嶋 具教(物質・材料研究機構)、小山 敏幸(名古屋大学)

3:20 PM - 3:35 PM

[110] Development of machine learning model for inverse analysis of anisotropy strength of interfacial energy from microsegregation

*Souta FUKUZAWA1, Ryo Yamada2, Munekazu Ohno2 (1. Graduated school, Hokkaido Univ, 2. Hokkaido Univ)

Keywords:フェーズフィールド法、機械学習、深層学習、逆問題、ニューラルネット

Development of machine learning model for inverse analysis of anisotropy strength of interfacial energy from microsegregation

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