文献
J-GLOBAL ID:201902211855850789
整理番号:19A2771138
牽引駆動システムにおけるDCリンクキャパシタの信頼性のためのアクティブ設計支援深層学習【JST・京大機械翻訳】
Active Design Aided Deep Learning for Reliability of DC-Link Capacitor in Traction Drive System
著者 (6件):
Yao Bo
(Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education,,Chengdu,,China)
,
Ge Xinglai
(Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education,,Chengdu,,China)
,
Shu Lingzhou
(School of Information and Software Engineering, University of Electronic Science and Technology of China,,,Chengdu,,China)
,
Zhang Yichi
(Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education,,Chengdu,,China)
,
Wang Huiming
(Southwest Jiaotong University,Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education,,Chengdu,,China)
,
Gou Bin
(Nanyang Technological University,the Rolls-Royce @ NTU Corporate Lab,,,,Singapore)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2019
号:
ITEC Asia-Pacific
ページ:
1-6
発行年:
2019年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)