Extreme Learning Machines: A new approach for prediction of reference evapotranspiration

Arid regions; Atmospheric temperature; Evapotranspiration; Geographical regions; Knowledge acquisition; Mean square error; Meteorology; Neural networks; Wind; Arid and semi-arid regions; Coefficient of determination; Extreme learning machine; Feedforward backpropagation; Generalization performance;...

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Bibliographic Details
Main Authors: Abdullah S.S., Malek M.A., Abdullah N.S., Kisi O., Yap K.S.
Other Authors: 57213171981
Format: Article
Published: Elsevier 2023
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Summary:Arid regions; Atmospheric temperature; Evapotranspiration; Geographical regions; Knowledge acquisition; Mean square error; Meteorology; Neural networks; Wind; Arid and semi-arid regions; Coefficient of determination; Extreme learning machine; Feedforward backpropagation; Generalization performance; Meteorological condition; Penman-Monteith equations; Reference evapotranspiration; Learning systems; air temperature; algorithm; evapotranspiration; learning; meteorology; new record; Penman-Monteith equation; performance assessment; semiarid region; Basra; Iraq