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Zapf, Fabian, Wallek, Thomas (2022) Case-study of a flowsheet simulation using deep-learning process models for multi-objective optimization of petrochemical production plants. Computers & Chemical Engineering, 162. 107823 doi:10.1016/j.compchemeng.2022.107823

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Reference TypeJournal (article/letter/editorial)
TitleCase-study of a flowsheet simulation using deep-learning process models for multi-objective optimization of petrochemical production plants
JournalComputers & Chemical Engineering
AuthorsZapf, FabianAuthor
Wallek, ThomasAuthor
Year2022 (June)Volume162
PublisherElsevier BV
DOIdoi:10.1016/j.compchemeng.2022.107823Search in ResearchGate
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Mindat Ref. ID14432881Long-form Identifiermindat:1:5:14432881:1
GUID0
Full ReferenceZapf, Fabian, Wallek, Thomas (2022) Case-study of a flowsheet simulation using deep-learning process models for multi-objective optimization of petrochemical production plants. Computers & Chemical Engineering, 162. 107823 doi:10.1016/j.compchemeng.2022.107823
Plain TextZapf, Fabian, Wallek, Thomas (2022) Case-study of a flowsheet simulation using deep-learning process models for multi-objective optimization of petrochemical production plants. Computers & Chemical Engineering, 162. 107823 doi:10.1016/j.compchemeng.2022.107823
In(2022) Computers & Chemical Engineering Vol. 162. Elsevier BV

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