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Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis [期刊论文]
Global Change Biology, 2020-01-01, 26 (3
Kim Y.;  Johnson M.S.;  Knox S.H.;  Black T.A.;  Dalmagro H.J.;  Kang M.;  Kim J.;  Baldocchi D.
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A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration [期刊论文]
Atmospheric Environment, 2020-01-01, 222
Berrocal V.J.;  Guan Y.;  Muyskens A.;  Wang H.;  Reich B.J.;  Mulholland J.A.;  Chang H.H.
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A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration [期刊论文]
Atmospheric Environment, 2020-01-01, 222
Berrocal V.J.;  Guan Y.;  Muyskens A.;  Wang H.;  Reich B.J.;  Mulholland J.A.;  Chang H.H.
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Downscaling of daily extreme temperatures in the Yarlung Zangbo River Basin using machine learning techniques [期刊论文]
THEORETICAL AND APPLIED CLIMATOLOGY, 2019-01-01, 136 (3-4) : 1275-1288
Ren, Meifang;  Pang, Bo;  Xu, Zongxue;  Yue, Jiajia;  Zhang, Rong
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Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques [期刊论文]
IET RENEWABLE POWER GENERATION, 2019-01-01, 13 (7) : 1009-1023
Akhter, Muhammad Naveed;  Mekhilef, Saad;  Mokhlis, Hazlie;  Shah, Noraisyah Mohamed
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Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region [期刊论文]
International Journal of Applied Earth Observation and Geoinformation, 2017-01-01, 58
Pôças I;  , Gonçalves J;  , Costa P;  M;  , Gonçalves I;  , Pereira L;  S;  , Cunha M
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Advanced identification and classification methods for Red Sea Troughs and their active phase, applied for related evolution scenarios and future changes prediction [项目]
Hadas Saaroni, Baruch Ziv, Pinhas Alpert
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A global prediction of seafloor sediment porosity using machine learning [期刊论文]
Geophysical Research Letters, 2015-01-01, 42 (24
Martin K.M.;  Wood W.T.;  Becker J.J.
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A Method for the Evaluation of Image Quality According to the Recognition Effectiveness of Objects in the Optical Remote Sensing Image Using Machine Learning Algorithm [期刊论文]
PLOS ONE, 2014-01-01, 9 (1
Tao Yuan;  Xinqi Zheng;  Xuan Hu;  Wei Zhou;  Wei Wang
Adobe PDF(2093Kb)  |  View/Download:2/1
 

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