Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Brian W Baetz"'
Engineering represents an ordered activity of creative design and inventive manufacture of ingenious devices. Its practitioners have thereby stimulated individuals, enlivened communities, enriched civilizations, and contributed to the shaping of cult
Publikováno v:
Renewable Energy. 151:1307-1317
Systematically evaluating the emission intensity and total emission of industries is indispensable for understanding energy and environmental sector performance in general and to support scientific climate change policy-making. In this study, an envi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00ba2ffc9a10998e803de17b0eb740f9
https://doi.org/10.1016/j.renene.2019.11.136
https://doi.org/10.1016/j.renene.2019.11.136
Publikováno v:
Water Resources Research. 57
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec0c2792feb48c42e2c38a28b22cb528
https://doi.org/10.1029/2021wr029731
https://doi.org/10.1029/2021wr029731
Autor:
David J. Kovacs, Zhong Li, Brian W. Baetz, Youngseck Hong, Sylvain Donnaz, Xiaokun Zhao, Pengxiao Zhou, Huihuang Ding, Qirong Dong
Publikováno v:
Journal of Membrane Science. 660:120817
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9aa2444474b6d05a0444e5ba3b460bce
https://doi.org/10.1016/j.memsci.2022.120817
https://doi.org/10.1016/j.memsci.2022.120817
Publikováno v:
Water Resources Research. 57
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fad0d34d4433c72d658dc59196317683
https://doi.org/10.1029/2020wr029149
https://doi.org/10.1029/2020wr029149
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 33:1781-1792
Influent flow of wastewater treatment plants (WWTPs) is a crucial variable for plant operation and management. In this study, a random forest (RF) model was applied for daily wastewater inflow prediction, and a new probabilistic prediction approach w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9242b012c860d9d4d25d8832ee87b565
https://doi.org/10.1007/s00477-019-01732-9
https://doi.org/10.1007/s00477-019-01732-9
Publikováno v:
Renewable and Sustainable Energy Reviews. 106:97-109
Facing the potential conflict between economic and environmental challenges, it is essential to investigate the integrated GHG emissions and the emission relationships of all industries in a socio-economic system to support formulation of industriall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5035bb27e1aeb2536443d1390a39b5ba
https://doi.org/10.1016/j.rser.2019.03.001
https://doi.org/10.1016/j.rser.2019.03.001
Publikováno v:
Applied Energy. 232:69-78
Industrial GHG mitigation policies are prevalent across the world to realize global greenhouse gas (GHG) emissions targets. It is essential to simulate the impacts of different policies on various industries in the socio-economic system to find out t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::115361505ad5f4290abf26e013034960
https://doi.org/10.1016/j.apenergy.2018.09.192
https://doi.org/10.1016/j.apenergy.2018.09.192
Feature importance has been a popular approach for machine learning models to investigate the relative significance of model predictors. In this study, we developed a Wilk's feature importance (WFI) method for hydrological inference. Compared with co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ab4d4793b27038186c800bfa9161736
https://doi.org/10.5194/hess-2021-65
https://doi.org/10.5194/hess-2021-65
Publikováno v:
Applied Energy. 229:493-504
This study developed an inexact optimization modelling approach for supporting regional energy systems decision-making and greenhouse gas emission mitigation under uncertainty. The developed model integrates multiple inexact optimization programming
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0adaa3f139c8a74786b37f8eafbd5036
https://doi.org/10.1016/j.apenergy.2018.06.140
https://doi.org/10.1016/j.apenergy.2018.06.140