Machine learning (ML) models have been widely used in the modeling, design and
prediction in energy systems. During the past two decades, there has been a dramatic …

During the past two decades of e-commerce growth, the concept of a business model has
become increasingly popular. More recently, the research on this realm has grown rapidly …

Huge amounts of data are circulating in the digital world in the era of the Industry 5.0
revolution. Machine learning is experiencing success in several sectors such as intelligent …

Rotating electrical machines are electromechanical energy converters with a fundamental
impact on the production and conversion of energy. Novelty and advancement in the control …

Restructuring of power systems along with the integration of renewable energy resources in
electricity networks have transformed traditional distribution networks (DNs) into new active …

In this study, a hybrid algorithm of adaptive neuro fuzzy inference system (ANFIS), particle
swarm optimization (PSO) and principle component analysis (PCA) is utilized to predict the …

In this paper, we present a Cluster-Based Approach (CBA) that utilizes the support vector
machine (SVM) and an artificial neural network (ANN) to estimate and predict the daily …

Current power systems are characterized by the increase of renewable generation and
distributed energy resources introducing more variability on the generation and enhancing …

Peer-to-peer (P2P) energy trading system has the ability to completely revolutionize the
current household energy system by sharing energy among residents. As the number of …

Electricity in the retail market has a different value for different types of consumers.
Therefore, different retail prices are usually determined for various consumers in the retail …