文献
J-GLOBAL ID:201802250417840891
整理番号:18A0551417
シミュレート触媒パラメータによる反応収率の予測のための機械学習法
Machine Learning Approach for Prediction of Reaction Yield with Simulated Catalyst Parameters
著者 (6件):
Yada Akira
(Interdisciplinary Research Center for Catalytic Chemistry, National Institute of Advanced Industrial Science and Technology (AIST))
,
Nagata Kenji
(Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST))
,
Ando Yasunobu
(Research Center for Computational Design of Advanced Functional Materials, National Institute of Advanced Industrial Science and Technology (AIST))
,
Matsumura Tarojiro
(Research Center for Computational Design of Advanced Functional Materials, National Institute of Advanced Industrial Science and Technology (AIST))
,
Ichinoseki Sakina
(Interdisciplinary Research Center for Catalytic Chemistry, National Institute of Advanced Industrial Science and Technology (AIST))
,
Sato Kazuhiko
(Interdisciplinary Research Center for Catalytic Chemistry, National Institute of Advanced Industrial Science and Technology (AIST))
資料名:
Chemistry Letters
(Chemistry Letters)
巻:
47
号:
3
ページ:
284-287(J-STAGE)
発行年:
2018年
JST資料番号:
S0742A
ISSN:
0366-7022
CODEN:
CMLTAG
資料種別:
逐次刊行物 (A)
記事区分:
短報
発行国:
日本 (JPN)
言語:
英語 (EN)