Data-driven modeling and learning in science and engineering

Francisco J. Montáns, Francisco Chinesta, Rafael Gómez-Bombarelli, J. Nathan Kutz
2019 Comptes rendus. Mecanique  
In the past, data in which science and engineering is based, was scarce and frequently obtained by experiments proposed to verify a given hypothesis. Each experiment was able to yield only very limited data. Today, data is abundant and abundantly collected in each single experiment at a very small cost. Data-driven modeling and scientific discovery is a change of paradigm on how many problems, both in science and engineering, are addressed. Some scientific fields have been using artificial
more » ... ligence for some time due to the inherent difficulty in obtaining laws and equations to describe some phenomena. However, today data-driven approaches are also flooding fields like mechanics and materials science, where the traditional approach seemed to be highly satisfactory. In this paper we review the application of data-driven modeling and model learning procedures to different fields in science and engineering.
doi:10.1016/j.crme.2019.11.009 fatcat:7rtlth7ncreqthugtduxtzjpky