Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

In the field of medical image analysis within deep learning (DL), the importance of
employing advanced DL techniques cannot be overstated. DL has achieved impressive …

Accurately modeling and forecasting electricity consumption remains a challenging task due
to the large number of the statistical properties that characterize this time series such as …

In the domain of using DL-based methods in medical and healthcare prediction systems, the
utilization of state-of-the-art deep learning (DL) methodologies assumes paramount …

Responding to the global call for sustainable renewable energy sources amidst growing
energy demands, exhaustion of fossil fuels, and increasing greenhouse gas emissions, this …

Nowadays, machine learning (ML) has attained a high level of achievement in many
contexts. Considering the significance of ML in medical and bioinformatics owing to its …

Most of the developed and developing countries around the world are delving into the
implementation of demand response (DR) strategies in demand side management (DSM) to …

Due to increasing environmental concerns and demand for clean energy resources,
photovoltaic (PV) systems are becoming more prevalent. Considering that in several …

This study employs soft computing techniques, including artificial neural network (ANN)
models and gene expression programming (GEP), to enhance the prediction of ultimate load …

Metamodeling is a promising technique for alleviating the computational burden of building
energy simulation. Although various machine learning (ML) algorithms have been applied …