Abstract Applications of Machine Learning methods make a paradigm shift in the domain of
water resources engineering. This study not only presents the story of emerging eXtreme …

The resilient modulus (MR) of various pavement materials plays a significant role in the
pavement design by a mechanistic-empirical method. The MR determination is done by …

Machine learning (ML) applications in hydrology are revolutionizing our understanding and
prediction of hydrological processes, driven by advancements in artificial intelligence and …

Diabetes mellitus is often a hyperglycemic condition that poses a substantial threat to human
health. Early diabetes detection decreases morbidity and mortality. Due to the scarcity of …

A novel investigation of the bearing capacity of ring footings embedded in undrained
anisotropic clays using a new hybrid soft computation technique that cooperates between …

Predictions of thermal performance (η) of flat plate solar collectors (FPSCs) can provide
essential information for diverse engineering applications such as thermal and energy …

Because of the overgrowth of data, especially in text format, the value and importance of
multi‐label text classification have increased. Aside from this, preprocessing and particularly …

Accurate water level forecasting is important to understand and provide an early warning of
flood risk and discharge. It is also crucial for many plants and animal species that needs …

Reference evapotranspiration can cause huge discrepancies in soil moisture and runoff
which is responsible for uncertainties in drought warning systems. Reference …

Natural streams longitudinal dispersion coefficient (Kx) is an essential indicator for pollutants
transport and its determination is very important. Kx is influenced by several parameters …