Predictive modeling is reshaping how businesses anticipate challenges, seize opportunities, and optimize processes. By leveraging machine learning, ensemble methods, and advanced analytics, ...

Recent advances in hydrological science highlight the urgent need for robust and adaptive modeling approaches to support effective disaster management in ...

The construction industry has always faced one persistent challenge—cost overruns. Budgeting for planned projects shows that ...

New data highlight predictive patient-derived models, resistance insights, and end-to-end translational workflows to improve translational oncology confidence ...

Artificial intelligence and machine learning are reshaping diabetes prevention, diagnosis, and management across the care continuum. Continuous glucose ...

It also plays a key role in understanding how intelligent AI is, preventing the misallocation of resources, and guiding ...

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Flood inundation models are tools that predict where water flows, how deep it gets, how fast it moves and how long it remains during a flood event. But despite recent advances in flood inundation ...

Abstract: Explicit model predictive direct speed control (EMP-DSC) for permanent magnet synchronous motors can achieve excellent control performance with high dynamics and high precision. However, the ...

1 Department of Mathematics & Statistical Sciences, Jackson State University, Jackson, MS, USA. 2 Department of Public Health, California State University, Fullerton ...

Abstract: In this paper, a model predictive based minimum DC-link voltage control (MP-mDVC) method is proposed to enhance both the reliability and dynamic performance of grid-connected converters ...