Neural Network Based

Neural networks are increasingly used to solve complex problems across diverse scientific domains, primarily aiming to improve efficiency and accuracy compared to traditional methods. Current research focuses on applying neural networks to optimization problems, physical system modeling (including robotics and fluid dynamics), and solving differential equations, often employing architectures tailored to specific tasks, such as those incorporating attention mechanisms or hierarchical learning strategies. These advancements offer significant potential for accelerating scientific computation, improving the accuracy of simulations, and enabling new applications in areas like sports analytics, control systems, and image processing.