Advancements in evaporation prediction: introducing the Gated Recurrent Unit–Multi-Kernel Extreme Learning Machine (MKELM)–Gaussian Process Regression (GPR) model

Advancements in evaporation prediction: introducing the Gated Recurrent Unit–Multi-Kernel Extreme Learning Machine (MKELM)–Gaussian Process Regression (GPR) model

Abstract Predicting evaporation is an essential topic in water resources management. It is critical to plan irrigation schedules, optimize hydropower production, and accurately calculate the overall water balance. Thus, researchers have developed many prediction models for predicting evaporation. De...

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Bibliographic Details
Main Authors: Sharareh Pourebrahim, Mohammad Ehteram, Mehrdad Hadipour, Ozgur Kisi, Ahmed El-Shafie, Ali Najah Ahmed, Jit Ern Chen
Format: Article
Language:English
Published: SpringerOpen 2024-12-01
Series:Environmental Sciences Europe
Subjects:
Evaporation prediction
Deep learning models
Feature selection
Nonstationary data
Online Access:https://doi.org/10.1186/s12302-024-01028-y
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https://doi.org/10.1186/s12302-024-01028-y

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