Wind turbine control systems have evolved significantly over the past decades, moving from simple classical controllers to sophisticated artificial intelligence-based strategies. Early utility-scale ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...

We may receive a commission on purchases made from links. The Nintendo Switch 2 had an explosive launch, selling over 6 million units in just under two months. Gamers have started gearing up as more ...

Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct strengths and limitations. SFT is ...

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...

Abstract: Direct Current (DC) motors are extensively used in industrial applications for their versatility in speed control and adaptability. This paper introduces a Reinforcement Learning (RL)-based ...

Abstract: This work is proposing a new approach for the design of PID controllers by employing a machine learning technique called Random Forest. Conventional design of a PID controller falls into an ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...