Physics-supervised deep learning-based optimization (PSDLO) with accuracy and efficiency.

ABSTRACT: Identifying efficient and accurate optimization algorithms is a long-desired goal for the scientific community. At present, a combination of evolutionary and deep-learning methods is widely used for optimization. In this paper, we demonstrate three cases involving different physics and conclude that no matter how accurate a deep-learning model is for a single, specific problem, a simple combination of evolutionary and deep-learning methods cannot achieve the desired optimization because of the intrinsic nature of the evolutionary method. We begin by using a physics-supervised deep-learning optimization algorithm (PSDLO) to supervise the results from the deep-learning model. We then intervene in the evolutionary process to eventually achieve simultaneous accuracy and efficiency. PSDLO is su

SUBMITTER: Li X 

PROVIDER: S-EPMC10466106 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature