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Artificial intelligence for smart energy systems in process industries
Qian, F.
Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China.
Bogle, D.
Department of Chemical Engineering, University College London, United Kingdom.
Wang, M.
Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, S1 3JD, United Kingdom.
Pistikopoulos, S.
Texas A&M University, United States.
Yan, Jinyue
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
ORCID iD:
0000-0003-0300-0762
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2022 (English)
In:
Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 324, article id 119684
Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
Elsevier Ltd , 2022. Vol. 324, article id 119684
National Category
Computer Sciences
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URN:
urn:nbn:se:mdh:diva-59752
DOI:
10.1016/j.apenergy.2022.119684
ISI:
000859460400002
Scopus ID:
2-s2.0-85135395451
OAI: oai:DiVA.org:mdh-59752
DiVA, id:
diva2:1687976
Available from:
2022-08-17
Created:
2022-08-17
Last updated:
2022-10-05
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