The growing menace of global warming and restrictions on access to water in each region is
a huge threat to global hydrological sustainability. Hence, the perspective at which …

Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …

Forecasting river water levels or streamflow water levels (SWL) is vital to optimising the
practical and sustainable use of available water resources. We propose a new deep …

Streamflow plays a major role in the optimal management and allocation of available water
resources in each region. Reliable techniques are therefore needed to be developed for …

This study aims to assess the spatiotemporal performance of Machine Learning-based
techniques for simulating streamflow on a continental scale using Long-Sort Term Memory …

Cimandiri watershed in Sukabumi prefecture of West Java, Indonesia, has been used for
profitable activities such as power plant, rafting tourism, drinking water, and municipal …

The prediction of diseases caused by viral infections is a complex medical task where many
real data that consists of different variables must be employed. As known, COVID-19 is the …

Accurate modeling of the rainfall-runoff process is still a challenging job despite the
availability of various modeling methods, such as data-driven or knowledge-driven …

Water has been used as an injected fluid for decades to improve oil recovery, commonly
known as waterflooding. Simulating this process is very expensive, especially for the post …

Prediction of water resources for future years takes much attention from the water resources
planners and relevant authorities. However, traditional computational models like hydrologic …