论文标题
使用机器学习改善飞机性能：评论
Improving aircraft performance using machine learning: a review
论文作者
论文摘要
这篇评论涵盖了机器学习（ML）的新发展，这些发展影响了航空工程的多学科领域，包括基本的流体动力学（实验和数值），空气动力学，声学，燃烧和结构性健康监测。我们回顾了艺术的状态，收集了不同航空航天学科的ML方法的优势和挑战，并提供了我们对未来机会的看法。 ML的基本概念和最相关的策略与航空工程中最相关的应用一起介绍，表明ML正在改善飞机的性能，并且这些技术在不久的将来会产生很大的影响。
This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (experimental and numerical), aerodynamics, acoustics, combustion and structural health monitoring. We review the state of the art, gathering the advantages and challenges of ML methods across different aerospace disciplines and provide our view on future opportunities. The basic concepts and the most relevant strategies for ML are presented together with the most relevant applications in aerospace engineering, revealing that ML is improving aircraft performance and that these techniques will have a large impact in the near future.
