This review article systematically summarizes the existing literature on utilizing machine
learning (ML) techniques for the control and monitoring of electric machine drives. It is …

This review paper systematically summarizes the existing literature on applying classical AI
techniques and advanced deep learning algorithms to electric machine drives. It is …

In the process of the “smart” house systems work, there is a need to process fuzzy input data.
The models based on the artificial neural networks are used to process fuzzy input data from …

Abstract The Pearl River Delta urban agglomeration (PRD) is the main body responsible for
achieving carbon neutrality in China. However, high carbon dioxide (CO2) emissions are …

Artificial Neural Networks (ANNs) have become an accepted approach for a wide range of
challenges. Meanwhile, the advancement of chip manufacturing processes is approaching …

Recently, the application of machine learning on embedded systems has drawn interest in
both the research community and industry because embedded systems located at the edge …

Suspicious mass traffic constantly evolves, making network behaviour tracing and structure
more complex. Neural networks yield promising results by considering a sufficient number of …

Over the last several decades, neuro-fuzzy systems (NFS) have been widely analyzed and
described in the literature because of their many advantages. They can model the …

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private
passenger transportation. However, there are still several technological barriers that hinder …

The growing significance of low-carbon city (LCC) in addressing climate change has
captured global scholarly attention. This study conducts a bibliometric analysis in the field of …