Machine learning algorithms are increasingly used in various remote sensing applications
due to their ability to identify nonlinear correlations. Ensemble algorithms have been …

To improve the monitoring of the electrical power grid, it is necessary to evaluate the
influence of contamination in relation to leakage current and its progression to a disruptive …

In the face of a growing global population, plant breeding is being used as a sustainable tool
for increasing food security. A wide range of high-throughput omics technologies have been …

Reference Evapotranspiration (ET o) is a complex, dynamic and non-linear hydrological
process. Accurate estimation of ET o has long been an eminent topic of interest in the …

Accurate ahead forecasting of reference evapotranspiration (ET o) is crucial for effective
irrigation scheduling and management of water resources on a regional scale. A variety of …

From last decade, Big data analytics and machine learning is a hotspot research area in the
domain of agriculture. Agriculture analytics is a data intensive multidisciplinary problem. Big …

Precise forecasting of reference evapotranspiration (ET0) is one of the critical initial steps in
determining crop water requirements, which contributes to the reliable management and …

Accurate prediction of electricity consumption is essential for providing actionable insights to
decision-makers for managing volume and potential trends in future energy consumption for …

Hydro-agrological research considers the reference evapotranspiration (ETo), driven by
meteorological variables, crucial for achieving precise irrigation in precision agriculture. ETo …

Accurate pre-harvest prediction of wheat yield through secondary traits helps to facilitate
plant breeding and reduce costs. Machine learning (ML) algorithms are increasingly applied …