In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …

The learning process and hyper-parameter optimization of artificial neural networks (ANNs)
and deep learning (DL) architectures is considered one of the most challenging machine …

Electric power forecasting plays a substantial role in the administration and balance of
current power systems. For this reason, accurate predictions of service demands are needed …

Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the
treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge …

Biogeography-based optimization (BBO) is an evolutionary algorithm which is inspired by
the migration of species between habitats. Almost 10 years have passed since the first BBO …

Load forecasting has always been an important part in the planning and operation of electric
utilities, ie both transmission and distribution companies. With technological advancement …

Accurate fruit classification is difficult to accomplish because of the similarities among the
various categories. In this paper, we proposed a novel fruit‐classification system, with the …

Currently, the technology associated with charging stations for electric vehicles (EV) needs
to be studied and improved to further encourage its implementation. This paper presents a …

Long-term load forecasting (LTLF) is an essential process for strategical planning of the
future needed extension in the power systems of any country. Besides, deep learning has …

Load forecasting impacts directly financial returns and information in electrical systems
planning. A promising approach to load forecasting is the Echo State Network (ESN), a …