This study contains a survey on the architecture of electric vehicles and an artificial neural
network application for prediction of energy consumption in all-electric vehicles. In this study …

In this study, supervised machine learning techniques like random forest (RF), K-nearest
neighbour (KNN), multiple linear regression (MLR), and artificial neural networks (ANNs) …

Lithium-ion batteries' state-of-charge prediction (SoC) cannot be directly measured due to
their chemical structure. Therefore, a prediction can be made using the measurable data of …

“Ovulation” is the part of reproductive cycle. As such the reproductive cycle is divided into
three phases:(1) Menstruation and the follicular phase,(2) ovulation phase, and (3) the luteal …

Power electronics equipment have become an inextricable part of human society. Due to its
merit of high efficiency, power electronics switch mode supply like rectifiers finds its …

In this paper, cutting-edge technology development tried to increase driving efficiency in
response to the dominant tendency in the electric vehicle sector. By using regenerative …

Electric vehicles are gaining popularity in India as a significant new trend in the automobile
industry. These vehicles play a crucial role in protecting our world from air pollution …

Regenerative braking is an important technology in electric vehicles (EVs) that absorbs
kinetic energy during deceleration or braking and transforms it back to electrical energy. This …

In this study, supervised machine learning techniques like random forest (RF), K-nearest
neighbour (KNN), multiple linear regression (MLR), and artificial neural networks (ANNs) …

This study contains a survey on the architecture of electric vehicles and an artificial neural
network application for prediction of energy consumption in all-electric vehicles. In this study …