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Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China

Agricultural and Forest Meteorology · 2018 · Vol. 263 · pp. 225–241
Junliang FanWenjun YueLifeng WuFucang ZhangHuanjie CaiXiukang WangXianghui LuYouzhen Xiang
Plant Water Relations and Carbon DynamicsSolar Radiation and PhotovoltaicsHydrological Forecasting Using AIEvapotranspirationWind speedSupport vector machineEnvironmental scienceExtreme learning machineGradient boostingDecision treeMeteorologyRandom forestIrrigation scheduling

Funding

  • National Natural Science Foundation of China
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528
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References
Trend analysis of reference evapotranspiration in the western half of Iran
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Extreme learning machine: Theory and applications
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The Nature Of Statistical Learning Theory~
IEEE Transactions on Neural Networks · 1997 · 913 citations
Random Forests
Machine Learning · 2001 · 121,242 citations
THE PERFORMANCE OF MUTUAL FUNDS IN THE PERIOD 1945–1964
The Journal of Finance · 1968 · 4,393 citations
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