文献
J-GLOBAL ID:202202243887104217
整理番号:22A0978719
最小歪を与える溶接シーケンスを予測するための機械学習モデルの使用【JST・京大機械翻訳】
Using Machine Learning Models to Predict Weld Sequence giving Minimum Distortion
著者 (8件):
Devaraj Jeyaganesh
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Ziout Aiman
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Qudeiri Jaber Abu
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Baalfaqih Rashfa
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Baalfaqh Nasmah
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Alahbabi Kanna
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Alnaqbi Maitha
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
,
Alhosan Noura
(UAE University,Department of Mechanical Engineering,Al Ain,UAE)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2022
号:
ASET
ページ:
1-6
発行年:
2022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)