Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area

Z Yin, X Wen, Q Feng, Z He, S Zou, L Yang - Hydrology Research, 2017 - iwaponline.com
Accurate estimation of evapotranspiration is vitally important for management of water
resources and environmental protection. This study investigated the accuracy of integrating …

Support-vector-machine-based models for modeling daily reference evapotranspiration with limited climatic data in extreme arid regions

X Wen, J Si, Z He, J Wu, H Shao, H Yu - Water resources management, 2015 - Springer
Evapotranspiration is a major factor that controls hydrological process and its accurate
estimation provides valuable information for water resources planning and management …

[HTML][HTML] Estimation of reference evapotranspiration using spatial and temporal machine learning approaches

A Rashid Niaghi, O Hassanijalilian, J Shiri - Hydrology, 2021 - mdpi.com
Evapotranspiration (ET) is widely employed to measure amounts of total water loss between
land and atmosphere due to its major contribution to water balance on both regional and …

SVM, ANFIS, regression and climate based models for reference evapotranspiration modeling using limited climatic data in a semi-arid highland environment

H Tabari, O Kisi, A Ezani, PH Talaee - Journal of Hydrology, 2012 - Elsevier
The accurate estimation of reference evapotranspiration (ETo) becomes imperative in the
planning and management of irrigation practices. The Penman–Monteith FAO 56 (PMF-56) …

Prediction of hourly actual evapotranspiration using neural networks, genetic programming, and statistical models

Z Izadifar, A Elshorbagy - Hydrological processes, 2010 - Wiley Online Library
The complexity of the evapotranspiration process and its variability in time and space have
imposed some limitations on previously developed evapotranspiration models. In this study …

Evapotranspiration modeling using different tree based ensembled machine learning algorithm

Y Agrawal, M Kumar, S Ananthakrishnan… - Water Resources …, 2022 - Springer
The present study investigates and evaluate the scope and potential of modern computing
tools and techniques such as ensembled machine learning methods in estimating ETo. Five …

Assessment of data intelligence algorithms in modeling daily reference evapotranspiration under input data limitation scenarios in semi-arid climatic condition

J Rajput, M Singh, K Lal, M Khanna… - Water Science & …, 2023 - iwaponline.com
Crop evapotranspiration is essential for planning and designing an efficient irrigation
system. The present investigation assessed the capability of four machine learning …

[PDF][PDF] Hybrid of artificial neural network-genetic algorithm for prediction of reference evapotranspiration (ET^ sub 0^) in arid and semiarid regions

SS Abdullah, MA Malek, A Mustapha… - Journal of Agricultural …, 2014 - academia.edu
Evapotranspiration is a principal requirement in designing any irrigation project, especially
in arid and semiarid regions. Precise prediction of Evapotranspiration would reduce the …

Machine learning models for the estimation of monthly mean daily reference evapotranspiration based on cross-station and synthetic data

L Wu, Y Peng, J Fan, Y Wang - Hydrology Research, 2019 - iwaponline.com
The estimation of reference evapotranspiration (ET0) is important in hydrology research,
irrigation scheduling design and water resources management. This study explored the …

A novel integrated method based on a machine learning model for estimating evapotranspiration in dryland

T Fu, X Li, R Jia, L Feng - Journal of Hydrology, 2021 - Elsevier
Evapotranspiration (ET) plays a vital role in the water cycle and energy cycle and serves as
an important linkage between ecological and hydrological processes. Accurate estimation of …