Machine Learning in Chemical Engineering : A Perspective

Authors :: Erik Esche
Jens-Uwe Repke
Asja Fischer
Artur M. Schweidtmann
Sebastian Sager
Marius Kloft
Alexander Mitsos
Source :: Chemie-Ingenieur-Technik 93(12), 2029-2039 (2021). doi:10.1002/cite.202100083, Chemie-Ingenieur-Technik 93(12), 2029-2039 (2021). doi:10.1002/cite.202100083 special issue: "Special Issue: Artificial Intelligence in Chemical Engineering / Issue edited by: Michael Bortz, Kai Dadhe, Alexander Mitsos"
Publication Year :: 2021
Publisher :: RWTH Aachen University, 2021.
Abstract: Chemie - Ingenieur - Technik (2021). doi:10.1002/cite.202100083<br />Published by Wiley-VCH Verl., Weinheim

Subjects :: Knowledge representation and reasoning
business.industry
General Chemical Engineering
Deep learning
media_common.quotation_subject
General Chemistry
Machine learning
computer.software_genre
Creativity
Industrial and Manufacturing Engineering
Perspective (geometry)
Chemical engineering
ddc:660
Reinforcement learning
Artificial intelligence
business
computer
media_common
Optimal decision

Language :: English
Database :: OpenAIRE
Journal :: Chemie-Ingenieur-Technik 93(12), 2029-2039 (2021). doi:10.1002/cite.202100083, Chemie-Ingenieur-Technik 93(12), 2029-2039 (2021). doi:10.1002/cite.202100083 special issue: "Special Issue: Artificial Intelligence in Chemical Engineering / Issue edited by: Michael Bortz, Kai Dadhe, Alexander Mitsos"
Accession number :: edsair.doi.dedup.....e1b1c02c19120e654eab64ea32df2286
Full Text :: https://doi.org/10.18154/rwth-2021-09826