Author:
Montáns Francisco J.,Cueto Elías,Bathe Klaus-Jürgen
Abstract
AbstractThe extraordinary success of Machine Learning (ML) in many complex heuristic fields has promoted its introduction in more analytical engineering fields, improving or substituting many established approaches in Computer Aided Engineering (CAE), and also solving long-standing problems. In this chapter, we first review the ideas behind the most used ML approaches in CAE, and then discuss a variety of different applications which have been traditionally addressed using classical approaches and that now are increasingly the focus of ML methods.
Publisher
Springer International Publishing