A generalized belief interval-valued soft set with applications in decision making

Cheng, C; Cao, Z; Xiao, F

A generalized belief interval-valued soft set with applications in decision making

Cheng, C Cao, Z

Xiao, F

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Publisher:: SPRINGER
Publication Type:: Journal Article
Citation:: Soft Computing, 2020, 24, (13), pp. 9339-9350
Issue Date:: 2020-07-01

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Field	Value	Language
dc.contributor.author	Cheng, C
dc.contributor.author	Cao, Z https://orcid.org/0000-0003-3656-0328
dc.contributor.author	Xiao, F
dc.date.accessioned	2020-10-16T20:00:30Z
dc.date.available	2020-10-16T20:00:30Z
dc.date.issued	2020-07-01
dc.identifier.citation	Soft Computing, 2020, 24, (13), pp. 9339-9350
dc.identifier.issn	1432-7643
dc.identifier.issn	1433-7479
dc.identifier.uri	http://hdl.handle.net/10453/143312
dc.description.abstract	© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. The belief interval-valued soft set (BIVSS) combines soft set theory and belief interval value (Dempster–Shafer theory). In this study, we propose a generalized belief interval-valued soft set (GBIVSS) approach and explore the associated properties of this approach in decision-making applications. Using the score function, the scoring function and similarity measure used to compare the relationships between GBIVSS are proposed. Then, we applied the GBIVSS to deal with multi-attribute decision making (MADM) problems. Furthermore, we used a case study of car purchase to illustrate the rationality of the proposed approach. In addition, we compare the effectiveness and advantages of our proposed approach and other existing models, which show superior performance in our proposed approach. GBIVSS provides a solution for multi-attribute problems.
dc.language	English
dc.publisher	SPRINGER
dc.relation.ispartof	Soft Computing
dc.relation.isbasedon	10.1007/s00500-020-04949-x
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	A generalized belief interval-valued soft set with applications in decision making
dc.type	Journal Article
utslib.citation.volume	24
utslib.for	0102 Applied Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
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 Computer Science
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-10-16T20:00:13Z
pubs.issue	13
pubs.publication-status	Published
pubs.volume	24
utslib.citation.issue	13

Abstract:

© 2020, Springer-Verlag GmbH Germany, part of Springer Nature. The belief interval-valued soft set (BIVSS) combines soft set theory and belief interval value (Dempster–Shafer theory). In this study, we propose a generalized belief interval-valued soft set (GBIVSS) approach and explore the associated properties of this approach in decision-making applications. Using the score function, the scoring function and similarity measure used to compare the relationships between GBIVSS are proposed. Then, we applied the GBIVSS to deal with multi-attribute decision making (MADM) problems. Furthermore, we used a case study of car purchase to illustrate the rationality of the proposed approach. In addition, we compare the effectiveness and advantages of our proposed approach and other existing models, which show superior performance in our proposed approach. GBIVSS provides a solution for multi-attribute problems.

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http://hdl.handle.net/10453/143312