In the last few decades, a broad strand of literature in finance has implemented artificial
neural networks as a forecasting method. The major advantage of this approach is the …

Short-term water demand forecasting (StWDF) is the foundation stone in the derivation of an
optimal plan for controlling water supply systems. Deep learning (DL) approaches provide …

The current study intends to investigate a novel drug delivery system (DDS) based on
niosomes structure (NISM) and bovine serum albumin (BSA) which was formulated to BSA …

Accurate electricity forecasting has become a very important research field for high-
efficiency electricity production. But the hybrid data-driven models for load forecasting are …

Accurately modelling and predicting forest transpiration under changing environment and
canopy structure are essential for understanding the interactions among the atmosphere …

Multi-step time-series prediction is an essential supportive step for decision-makers in
several industrial areas. Artificial intelligence techniques, which use a neural network …

Water quality is a concern in most river basins worldwide due to the widespread release of
pollutants which impacts the freshwater ecosystems. Exploring the relationships between …

An ensemble artificial neural network (ENN) based hybrid function approximator (named
PEK), integrating the partial mutual information (PMI) based separate input variable …

To date, no previous studies based on the Coordinated Regional Climate Downscaling
Experiment Southeast Asia (CORDEX-SEA), which represents the most comprehensive set …

Modeling soil-water regime and solute transport in the vadose zone is strategic for
estimating agricultural productivity and optimizing irrigation water management. Direct …