Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …

Early prediction of grain yield helps scientists to make better breeding decisions for wheat.
Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based …

Uncertainty quantification (UQ) is an important benchmark to assess the performance of
artificial intelligence (AI) and particularly deep learning ensembled-based models. However …

Predicting crop yield is an important issue for farmers. Food security is important for decision-
makers. The agriculture industry can more accurately supply human demand for food if the …

High-throughput estimation of phenotypic traits from UAV (unmanned aerial vehicle) images
is helpful to improve the screening efficiency of breeding maize. Accurately estimating …

Pan evaporation (E p) is an efficient and practical tool for planning and managing water
resources, understanding the water balance in hydrological processes, and developing …

Due to its heterogeneous and complex nature, groundwater modeling needs great effort to
quantify the aquifer, a crucial tool for policymakers and hydrogeologists to understand the …

Quantitative remote sensing is a technique for quantitatively inferring or inverting earth
environmental variable from the original remote sensing observations, it is an important step …

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 …

Precise estimation of groundwater level (GWL) might be of great importance for attaining
sustainable development goals and integrated water resources management. Compared …