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Artificial intelligence for smart energy systems in process industries
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China.
Department of Chemical Engineering, University College London, United Kingdom.
Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, S1 3JD, United Kingdom.
Texas A&M University, United States.
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2022 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 324, article id 119684Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
Elsevier Ltd , 2022. Vol. 324, article id 119684
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Computer Sciences
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URN: urn:nbn:se:mdh:diva-59752DOI: 10.1016/j.apenergy.2022.119684ISI: 000859460400002Scopus ID: 2-s2.0-85135395451OAI: oai:DiVA.org:mdh-59752DiVA, id: diva2:1687976
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-10-05Bibliographically approved

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Yan, Jinyue

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