Artificial Intelligence (AI) is now entering every sub-field of science, technology, engineering, arts, and management. Thanks to the hype and availability of research funds, it is being adapted in many fields without much thought. Computational Science and Engineering (CS&E) is one such sub-field. By highlighting some critical questions around the issues and challenges in adapting Machine Learning (ML) for CS&E, most of which are often overlooked in journal papers, this contribution hopes to offer some insights into the adaptation of ML for applications in CS\&E and related fields. This is a general-purpose article written for a general audience and researchers new to the fields of ML and/or CS\&E. This work focuses only on the forward problems in computational science and engineering. Some basic equations and MATLAB code are also provided to help the reader understand the basics.
翻译:目前,人工智能(AI)正在进入科学、技术、工程、艺术和管理的每一个子领域,由于研究资金的杂交和可用性,它正在许多领域进行修改,没有经过太多的思考。计算科学和工程(CS&E)就是这样的一个子领域。通过突出围绕使机器学习适应CS&E的问题和挑战的一些关键问题,其中大部分经常在日记论文中被忽视,这一贡献希望对ML适应CS ⁇ E和相关领域的应用提供一些了解。这是为普通观众和研究人员撰写的通用文章,新到ML和/或CS ⁇ E领域。这项工作只侧重于计算科学和工程方面的前期问题。还提供一些基本方程式和MATLAB代码,帮助读者了解基本原理。