Economic Model Predictive Control (EMPC) represents an evolution of traditional control strategies, where the primary objective is to directly optimise an economic cost function rather than merely ...

Model Predictive Control (MPC) has emerged as a versatile and robust strategy in modern control engineering, enabling controllers to predict future system behaviour and optimise performance over a ...

Models built on machine learning in health care can be victims of their own success, according to researchers. Their study assessed the impact of implementing predictive models on the subsequent ...

Distributed model predictive control (DMPC) offers a computationally efficient alternative to centralized model predictive control (CMPC) for enabling the optimal control of industrial process systems ...

A group of researchers has developed and externally validated the first-ever predictive model to help clinicians identify ...

Predictive analytics is the study of historical data to make future predictions. It is a data analysis method that uses past ...

Metal-organic (MO) precursors are the chemical building blocks at the heart of atomically precise complex oxide materials.

A growing number of AI tools are being used to predict everything from sepsis to strokes, with the hope of accelerating the delivery of life-saving care. But over time, new research suggests, these ...

Intelligent agriculture requires precise, real-time control of diverse systems ranging from greenhouse climates to autonomous ...

Jet-powered humanoid iRonCub achieves simulated flight stability, paving the way for disaster-response and advanced robotics applications.

A local professor at Old Dominion University has created a disease forecasting model that predicts health crises, aiming to revolutionize healthcare strategies.