Data-Driven and AI-Enhanced Optimization Methods in Computational Science and Engineering

Resumen

This paper made a kind of design that is like a strong optimization thing using AI, it’s made for solving those very complex science and engineering problems that are usually hard. When doing many tests and simulations, this study found that the model works better than the old methods, like it gives faster result and more accurate also, and even if some noise comes, it still stays stable. The learning system in it kind of adjust by itself and works nice even when the computer power is not too high, which is cool actually. Also this framework show that it can work on many type of problems not just one or two. The multi goal solution part also show it can balance between many things like speed and accuracy. So this paper think that this AI based system can become a strong option for smart, adaptive and less resource heavy optimization method. In future maybe it can do more things like real time changing and used in many science areas.