文献
J-GLOBAL ID:202102255108459155
整理番号:21A0874224
ハイブリッド軌道場行列とマッピー記述子を用いた結晶材料特性予測のための畳込みニューラルネットワーク【JST・京大機械翻訳】
Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors
著者 (8件):
Cao Zhuo
(School of Mechanical Engineering, Guizhou University, Guiyang 550025, China)
,
Dan Yabo
(School of Mechanical Engineering, Guizhou University, Guiyang 550025, China)
,
Xiong Zheng
(Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA)
,
Niu Chengcheng
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guiyang 550025, China)
,
Li Xiang
(School of Mechanical Engineering, Guizhou University, Guiyang 550025, China)
,
Qian Songrong
(School of Mechanical Engineering, Guizhou University, Guiyang 550025, China)
,
Hu Jianjun
(School of Mechanical Engineering, Guizhou University, Guiyang 550025, China)
,
Hu Jianjun
(Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA)
資料名:
Crystals (Web)
(Crystals (Web))
巻:
9
号:
4
ページ:
191
発行年:
2019年
JST資料番号:
U7169A
ISSN:
2073-4352
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
スイス (CHE)
言語:
英語 (EN)