Power-draw prediction by random forest based on operating parameters for an industrial ball mill

Tohry, A Chehreh Chelgani, S Matin, SS Noormohammadi, M

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Field	Value	Language
dc.contributor.author	Tohry, A
dc.contributor.author	Chehreh Chelgani, S
dc.contributor.author	Matin, SS
dc.contributor.author	Noormohammadi, M
dc.date.accessioned	2021-06-22T01:04:57Z
dc.date.available	2021-06-22T01:04:57Z
dc.date.issued	2020-03
dc.identifier.citation	Advanced Powder Technology, 2020, 31, (3), pp. 967-972
dc.identifier.issn	0921-8831
dc.identifier.uri	http://hdl.handle.net/10453/149694
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	Advanced Powder Technology
dc.relation.isbasedon	10.1016/j.apt.2019.12.012
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0904 Chemical Engineering, 0913 Mechanical Engineering, 0914 Resources Engineering and Extractive Metallurgy
dc.subject.classification	Chemical Engineering
dc.title	Power-draw prediction by random forest based on operating parameters for an industrial ball mill
dc.type	Journal Article
utslib.citation.volume	31
utslib.for	0904 Chemical Engineering
utslib.for	0913 Mechanical Engineering
utslib.for	0914 Resources Engineering and Extractive Metallurgy
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	closed_access	*
dc.date.updated	2021-06-22T01:04:56Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	31
utslib.citation.issue	3

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