Multi‐valued interval neutrosophic linguistic soft set theory and its application in knowledge management. Issue 3 (4th August 2020)

• Record Type: Journal Article
• Authors: Mohd Kamal, Nor Liyana Amalini; Abdullah, Lazim; Abdullah, Ilyani; Saqlain, Muhammad
• Is Part Of: CAAI transactions on intelligence technology. Volume 5:Issue 3(2020)
• Page Start: 200
• Page End: 208
• Publication Date: 2020-08-04
• Subjects: set theory -- knowledge management -- decision making -- computational linguistics; knowledge management -- multicriteria decision‐making method -- multivalued interval neutrosophic linguistic soft weighted arithmetic averaging operator -- linguistic membership -- MVINLSS -- multivalued interval neutrosophic linguistic soft set theory; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2020.0036
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : This study proposed the concepts of a multi‐valued interval neutrosophic linguistic soft set (MVINLSS) by integrating the concepts of multi‐valued interval neutrosophic soft set and linguistic set. MVINLSS is presented as it can deal with ambiguous and uncertain information in decision making which is characterised by linguistic membership. This proposed set amalgamates quantitative assessment with the qualitative assessment which can solve complex problems with ambiguity, uncertainty, and inconsistency. It can be an effective tool to describe the real decision‐makers' opinions and reflect their hesitancy. Then, the authors propose the basic operational rules of MVINLSS. Moreover, they define a multi‐valued interval neutrosophic linguistic soft weighted arithmetic averaging operator. This work proposed a multi‐criteria decision‐making (MCDM) method which considers different priority levels of criteria and the criteria values take the form of multi‐valued interval neutrosophic linguistic soft numbers. Finally, the proposed MCDM method is applied to the knowledge management case, considering 11 criteria.