A novel model based on similarity measure and quality function deployment on interval neutrosophic sets for evaluation and selection market segments

Duong, Truong Thi Thuy; Phong, Lê Thái; Lê, Q; Thảo, Nguyễn Xuân

doi:10.3233/jifs-191790

Cited by 7 publications

(2 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In most research, similarity measures are constructed based on the distance measure and entropy [33][34][35]. However, as a fuzzy connective, the fuzzy equivalence has been used to depict the similarity between fuzzy sets from another aspect.…”

Section: Introductionmentioning

confidence: 99%

Similarity Measure for Interval Neutrosophic Sets and Its Decision Application in Resource Offloading of Edge Computing

et al. 2023

View full text Add to dashboard Cite

Interval neutrosophic sets (INSs), characterized by truth, indeterminacy and falsity membership degrees, handle the uncertain and inconsistent information that commonly exists in real-life systems, and constitute an extension of the interval valued fuzzy set and interval valued intuitionistic fuzzy set. The existing works on similarity measures for INSs are mostly constructed by distance measures and entropies. Meanwhile, the degree of similarity is expressed as a single number, even if the interval-valued information is considered. This may lead to a loss of interval-valued information. In order to cope with these issues, in this paper, we introduce a new approach to constructing the similarity measures for INSs using fuzzy equivalencies. First, based on fuzzy equivalencies and aggregation operators, the definition of interval-valued fuzzy equivalence is generalized to interval neutrosophic values. Then, based on the framework of INSs, we propose the definition and construction method of the similarity measure using the interval neutrosophic fuzzy equivalence. The similarity degree is expressed as an interval and could retain more information than ever before. In addition, according to practical situations, one can obtain different similarities by selecting the parameters in fuzzy equivalence. Due to the increase in edge computing, it is necessary to reasonably offload the client’s resource and assign them to the edge server to balance the resource usage. The Similarity measure is conductive to select and match the client and edge server. Finally, an illustrative example verifies that the proposed method can find a reasonable client and edge server, as well as effectiveness in the edge computing application.

show abstract

Section: Introductionmentioning

confidence: 99%

Similarity Measure for Interval Neutrosophic Sets and Its Decision Application in Resource Offloading of Edge Computing

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Ever since Smith (1956) presented the benefits of market segment, numerous studies have been investigated in evaluating and selecting market segments (McDonald and Dunbar, 2004;Quinn and Dibb, 2010;Aghdaie et al, 2013;Ghorabaee et al, 2017;Duong et al, 2020). With a view to evaluating a variety of market segments, decision makers are required to take into account appropriate criteria during the selection process.…”

Section: Introductionmentioning

confidence: 99%

TOPSIS model based on entropy and similarity measure for market segment selection and evaluation

Duong

Thảo

2021

AJEB

Self Cite

View full text Add to dashboard Cite

PurposeThe paper aims to propose a practical model for market segment selection and evaluation. The paper carries out a technique of order preference similarity to the ideal solution (TOPSIS) approach to make an operation systematic dealing with multi-criteria decision- making problem.Design/methodology/approachIntroducing a multi-criteria decision-making problem based on TOPSIS approach. A new entropy and new similarity measure under neutrosopic environment are proposed to evaluate the weights of criteria and the relative closeness coefficient in TOPSIS model.FindingsThe outcomes show that the TOPSIS model based on new entropy and similarity measure is effective for evaluation and selection market segment. Profitability, growth of the market, the likelihood of sustainable differential advantages are the most important insights of criteria.Originality/valueThis paper put forward an effective multi-criteria decision-making dealing with uncertain information.

show abstract

A novel dissimilarity measure on picture fuzzy sets and its application in multi-criteria decision making

Duong

Thảo

2020

Soft Comput

View full text Add to dashboard Cite

A novel model based on similarity measure and quality function deployment on interval neutrosophic sets for evaluation and selection market segments

Cited by 7 publications

References 31 publications

Similarity Measure for Interval Neutrosophic Sets and Its Decision Application in Resource Offloading of Edge Computing

Similarity Measure for Interval Neutrosophic Sets and Its Decision Application in Resource Offloading of Edge Computing

TOPSIS model based on entropy and similarity measure for market segment selection and evaluation

A novel dissimilarity measure on picture fuzzy sets and its application in multi-criteria decision making

Contact Info

Product

Resources

About