Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...
A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, ...
Kauai, one of the most remote islands of Hawaii, stands steady among the timeless crash of ocean waves. Electric waves, ...
A new synthesis of seismic research shows that artificial intelligence, when combined with physical principles, is rapidly ...
Published in Acta Mechanica Sinica, this forward-looking study argues that embedding physical laws into AI models is ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
Researchers from the University of Chinese Academy of Sciences and collaborating institutions have developed a novel ...
Researchers at Shanghai University have developed a physics-constrained, data-efficient artificial intelligence framework ...
Abstract: This paper proposes a novel multi physics informed neural network-based model predictive control (MPINN-MPC) strategy to address torsional vibrations and torque fluctuations during electric ...
1 College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, China 2 Xinjiang Key Laboratory of Water Engineering Safety and Water Disaster Prevention, Urumqi, ...
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