Abstract: Synchronous machines are fundamental components. Accurate modelling of nonlinear magnetic saturation characteristics is essential. Traditional models often rely on computationally intensive ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

Abstract: This paper proposes a design strategy of surface-mounted permanent magnet synchronous machine (SPMSM) targeting a specified constant power speed range (CPSR). The pivotal role of permanent ...

You will be redirected to our submission process. Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many data-scarce regions.

You will be redirected to our submission process. The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to unravel the complexity ...

Code examples and implementations from the book "AI in Climate Science: Machine Learning for Environmental Modeling and Prediction" by Prof. Sandeep Gupta, Prof. Budesh Kanwer, and Prof. Badrul Hisham ...

Feb. 21, 2026 Researchers have mapped the genetic risk of hemochromatosis across the UK and Ireland for the first time, uncovering striking hotspots in north-west Ireland and the Outer Hebrides. In ...