文献
J-GLOBAL ID:202202243143634196
整理番号:22A1180145
長期平均月露点温度を予測するためのランダムフォレストと多変量適応回帰スプラインの実現可能性【JST・京大機械翻訳】
Feasibility of Random Forest and Multivariate Adaptive Regression Splines for Predicting Long-Term Mean Monthly Dew Point Temperature
著者 (8件):
Zhang Guodao
(1College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China)
,
Bateni Sayed M.
(2Department of Civil and Environmental Engineering and Water Resources Research Center, University of Hawaii at Manoa, Honolulu, HI, United States)
,
Jun Changhyun
(3Department of Civil and Environmental Engineering, College of Engineering, Chung-Ang University, Seoul, Korea)
,
Khoshkam Helaleh
(2Department of Civil and Environmental Engineering and Water Resources Research Center, University of Hawaii at Manoa, Honolulu, HI, United States)
,
Band Shahab S.
(4Future Technology Research Center, National Yunlin University of Science and Technology, Douliou, Taiwan)
,
Mosavi Amir
(5John von Neumann Faculty of Informatics, Obuda University, Budapest, Hungary)
,
Mosavi Amir
(6Institute of Information Society, University of Public Service, Budapest, Hungary)
,
Mosavi Amir
(7Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, Bratislava, Slovakia)
資料名:
Frontiers in Environmental Science (Web)
(Frontiers in Environmental Science (Web))
巻:
10
ページ:
826165
発行年:
2022年
JST資料番号:
U7070A
ISSN:
2296-665X
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)