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pro vyhledávání: '"Laurens Lueg"'
Autor:
Dominik Schack, Michael Bortz, Laurens Lueg, Martin von Kurnatowski, Robin Schmidt, Patrick Otto Ludl
Publikováno v:
Chemie Ingenieur Technik. 93:2052-2062
Process simulation based on physical models often faces computational problems with respect to convergence, especially if the underlying flowsheets are complex. The use of data-driven surrogate models connected to flowsheets promises to overcome thes
Autor:
Patrick Otto Ludl, Robin Schmidt, Laurens Lueg, Martin von Kurnatowski, Michael Bortz, Patricia Bickert, Dominik Schack, Evrim Örs
Publikováno v:
31st European Symposium on Computer Aided Process Engineering ISBN: 9780323885065
Process design based on physical models often faces computational problems with respect to convergence, especially if the underlying flowsheets are complex. The use of data-driven surrogate models promises to overcome these challenges. This contribut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c70c47635436bc55f5e2361e67038ec1
https://doi.org/10.1016/b978-0-323-88506-5.50156-x
https://doi.org/10.1016/b978-0-323-88506-5.50156-x
Clustering and classification critically rely on distance metrics that provide meaningful comparisons between data points. To this end, learning optimal distance functions from data, known as metric learning, aims to facilitate supervised classificat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef4bf175a7ecd93eef5e7ab4aaa1c4d2
http://arxiv.org/abs/1803.10647
http://arxiv.org/abs/1803.10647