In the current study, an ability of a novel regression-based method is evaluated in modeling
daily reference evapotranspiration (ET0), which is an important issue in water resources …

This paper investigates the potential of back propagation neural network and M5 model tree
based regression approaches to model monthly reference evapotranspiration using climatic …

Modeling reference evapotranspiration (ET 0) is important in reservoir management,
planning regional water resources and evaluation of drinking-water supplies. The study …

This paper investigates the potential of M5 model tree based regression approach to model
daily reference evapotranspiration using climatic data of Davis station maintained by …

In this study, the predictive power of three different machine learning (ML)-based
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …

Evaporation is a fundamental parameter in the hydrological cycle. This study examines the
performance of M5 model tree and artificial neural network (ANN) models in estimating …

This paper aimed to estimate the reference evapotranspiration (ET0) due to some limitations
of the Food and Agriculture Organization-56 Penman-Monteith (FAO 56-PM) approach by …

The study aimed to evaluate the accuracy of empirical equations (Hargreaves-Samani; HS,
Irmak; IR and Dalton; DT) and multivariate linear regression models (MLR1–6) for estimating …

Reference evapotranspiration (ET0) estimates are commonly used in hydrologic planning
for water resources and agricultural applications. Last 2 decades, machine learning (ML) …

The increasing frequency of droughts and floods due to climate change has severely
affected water resources across the globe in recent years. An optimal design for the …