文献
J-GLOBAL ID:202202241226869840
整理番号:22A0435456
世帯のリバウンド関連環境フットプリントを評価するための新しい機械学習アプローチと共同住宅への適用【JST・京大機械翻訳】
A novel machine-learning approach for evaluating rebounds-associated environmental footprint of households and application to cooperative housing
著者 (6件):
Shinde Rhythima
(Swiss Federal Institute of Technology, ETH Zurich, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Ecological Systems Design, John-von-Neumann-Weg 9, 8093, Zuerich, Switzerland)
,
Froemelt Andreas
(Swiss Federal Institute of Technology, ETH Zurich, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Ecological Systems Design, John-von-Neumann-Weg 9, 8093, Zuerich, Switzerland)
,
Froemelt Andreas
(Future Cities Lab Global, Zurich Hub, Singapore-ETH Centre at CREATE, Switzerland)
,
Kim Aleksandra
(Swiss Federal Institute of Technology, ETH Zurich, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Ecological Systems Design, John-von-Neumann-Weg 9, 8093, Zuerich, Switzerland)
,
Kim Aleksandra
(Paul Scherrer Institute, Technology Assessment Group, Forschungsstrasse 111, 5232, Villigen PSI, Switzerland)
,
Hellweg Stefanie
(Swiss Federal Institute of Technology, ETH Zurich, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, Ecological Systems Design, John-von-Neumann-Weg 9, 8093, Zuerich, Switzerland)
資料名:
Journal of Environmental Management
(Journal of Environmental Management)
巻:
304
ページ:
Null
発行年:
2022年
JST資料番号:
H0435B
ISSN:
0301-4797
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)