This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...

Researchers have successfully performed the world's first Milky Way simulation that accurately represents more than 100 billion individual stars over the course of 10 thousand years. This feat was ...

Researchers combined deep learning with high-resolution physics to create the first Milky Way model that tracks over 100 billion stars individually. Their AI learned how gas behaves after supernovae, ...

For more than a decade, researchers have wondered whether artificial intelligence could help predict what incapacitated patients might want when doctors must make life-or-death decisions on their ...

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...

This project develops advanced machine learning surrogate models for predicting distillate purity (xD) and reboiler duty (QR) in ethanol-water binary distillation columns. By combining rigorous ...

University of Sheffield researchers developed a machine learning framework to improve coating properties in a roll-to-roll slot die coating process. The work is seen as an initial step toward broader ...

Abstract: The machine learning method for surrogate modeling is a keystone in surrogate model-assisted evolutionary algorithms (SAEAs). The current arguably most widely used surrogate modeling methods ...

Abstract: Permanent magnet arc motor (PMAM) has gained increasing prominence in the industrial applications. To enhance the motor performance of PMAM, the surrogate modeling and optimal design are ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Scientists have developed an AI-powered fluid simulation model that significantly reduces computation time while maintaining accuracy. Their approach could aid offshore power generation, ship design ...