Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …

Topology optimization (TO) is a method of deriving an optimal design that satisfies a given
load and boundary conditions within a design domain. This method enables effective design …

The development of technologies for the additive manufacturing, in particular of metallic
materials, is offering the possibility of producing parts with complex geometries. This opens …

Photovoltaic power generation (PVPG) forecasting has attracted increasing research and
industry attention due to its significance for energy management, infrastructure planning …

This paper reviews the recent developments of design optimization methods for
electromagnetic devices, with a focus on machine learning methods. First, the recent …

Switched reluctance machines (SRMs) have recently attracted more interest in many
applications due to the volatile prices of rare-earth permanent magnets (PMs) used in …

Reinforcement learning (RL) is popularly used for the development of an orderly charging
strategy for electric vehicles (EVs). However, a new environment (eg, charging areas and …

Employing machine learning techniques in predicting the parameters of metamaterial
antennas has a significant impact on the reduction of the time needed to design an antenna …

Electric motors find widespread application across various industrial fields. The pursuit of
enhanced comprehensive electric motors performance has consistently drawn significant …

With growing environmental concerns and the limitations of fuel cell resources, replacing
petrol-based engines with electric machines as the traction motor for electric vehicles (EVs) …