OWA operators in the calculation of the average green-house gases emissions

Amirbagheri, K; Merigó, JM; Guitart-Tarrés, L; Nuñez-Carballosa, A

OWA operators in the calculation of the average green-house gases emissions

Amirbagheri, K Merigó, JM Guitart-Tarrés, L Nuñez-Carballosa, A

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Publisher:: IOS PRESS
Publication Type:: Journal Article
Citation:: Journal of Intelligent and Fuzzy Systems, 2020, 38, (5), pp. 5427-5439
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Amirbagheri, K
dc.contributor.author	Merigó, JM
dc.contributor.author	Guitart-Tarrés, L
dc.contributor.author	Nuñez-Carballosa, A
dc.date.accessioned	2021-06-03T06:26:24Z
dc.date.available	2021-06-03T06:26:24Z
dc.date.issued	2020-01-01
dc.identifier.citation	Journal of Intelligent and Fuzzy Systems, 2020, 38, (5), pp. 5427-5439
dc.identifier.issn	1064-1246
dc.identifier.issn	1875-8967
dc.identifier.uri	http://hdl.handle.net/10453/149392
dc.description.abstract	This study proposes, through weighted averages and ordered weighted averaging operators, a new aggregation system for the investigation of average gases emissions. We present the ordered weighted averaging operators gases emissions, the induced ordered weighted averaging operators gases emissions, the weighted ordered weighted averaging operators gases emissions and the induced probabilistic weighted ordered weighted averaging operators gases emissions. These operators represent a new way of analyzing the average gases emissions of different variables like countries or regions. The work presents further generalizations by using generalized and quasi-arithmetic means. The article also presents an illustrative example with respect to the calculations of the average gases emissions in the European region.
dc.language	English
dc.publisher	IOS PRESS
dc.relation.ispartof	Journal of Intelligent and Fuzzy Systems
dc.relation.isbasedon	10.3233/JIFS-179635
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	OWA operators in the calculation of the average green-house gases emissions
dc.type	Journal Article
utslib.citation.volume	38
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
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	*
pubs.consider-herdc	false
dc.date.updated	2021-06-03T06:26:23Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	38
utslib.citation.issue	5

Abstract:

This study proposes, through weighted averages and ordered weighted averaging operators, a new aggregation system for the investigation of average gases emissions. We present the ordered weighted averaging operators gases emissions, the induced ordered weighted averaging operators gases emissions, the weighted ordered weighted averaging operators gases emissions and the induced probabilistic weighted ordered weighted averaging operators gases emissions. These operators represent a new way of analyzing the average gases emissions of different variables like countries or regions. The work presents further generalizations by using generalized and quasi-arithmetic means. The article also presents an illustrative example with respect to the calculations of the average gases emissions in the European region.

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http://hdl.handle.net/10453/149392