A novel distance measure on q-rung picture fuzzy sets and its application to decision making and classification problems

Pınar, Adem; Boran, Fatih Emre

doi:10.1007/s10462-021-09990-2

Cited by 31 publications

(13 citation statements)

References 39 publications

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“…This theory is used when we express the sum of membership, neutral, and nonmembership less than 1 It will not work for the case t + a + f > 1 SFS [15] It is better than PFS and PyFS. It works for the case t 2 + a 2 + f 2 < 1 It will not work for the case t 2 + a 2 + f 2 > 1 q-RPFS [17] It is better than PFS. It could handle when the sum of q-power of membership, neutral, and nonmembership is less than 1…”

Section: Discussionmentioning

confidence: 99%

“…Nonetheless, all of these ideas are subject to stringent limitations on the membership grade (MG) and nonmembership grade (NMG). Moreover, by including the neutral-membership grade in the abovementioned grades, we get the picture fuzzy sets (PFSs) [14], spherical fuzzy sets (SFSs) [15,16], m-polar spherical fuzzy sets (m-PSFSs) [12], and q-rung ortho picture fuzzy sets (q-RPFS) [17]. All these notions have some strict restrictions over the grade functions imposed on them.…”

Section: Introductionmentioning

confidence: 99%

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Spherical Linear Diophantine Fuzzy TOPSIS Algorithm for Green Supply Chain Management System

Alshammari

Parimala

Özel

et al. 2022

Journal of Function Spaces

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Enhancing competitive pressure is one of the most significant roles of supply chain management. The competitive environment and customer perception have shifted in favour of an ecological mentality. As a result, green supplier selection (GSS) has emerged as a critical problem. The challenge of green supplier selection striving for agility, durability, ecological sensitivity, leanness, and sustainability is tackled in this paper. In terms of recycling applications, environmental applications, carbon footprint, and water consumption, the environmental parameters evaluated in GSS and traditional supplier selection differ. Because of the form of the problem, a resolution is defined, which comprises an algorithm entrenched in the spherical linear Diophantine fuzzy sets (SLDFSs) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. Before discussing the approach of the SLDF model, some background information on SLDF sets is provided. To assure the uniqueness of this robust extension, different operations on SLDFSs are described, along with some concise interpretations to help the reader comprehend these ideas. A robust TOPSIS approach has been utilized in the issue of GSS by taking into consideration the multicriteria decision-making (MCDM) technique particularly useful in several areas, like analyzing and choosing traditional and environmental conventionalities. Due to linguistic criteria and the inability to assess all criteria, the fuzzy technique must be used with the TOPSIS method to lessen the consequences of instability and ambiguity. The spherical linear Diophantine fuzzy TOPSIS approach is employed, as it simplifies the evaluation of decision-makers and criteria. The hybrid technique resulting from integrating the SLDFS and TOPSIS is extremely successful in selecting which provider is more suited among the alternatives established on the criteria set by the order of significance, and this method may also be incorporated into similar issues.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spherical Linear Diophantine Fuzzy TOPSIS Algorithm for Green Supply Chain Management System

Alshammari

Parimala

Özel

et al. 2022

Journal of Function Spaces

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“…To fill the gaps of the existing distance measures of q-rung picture fuzzy sets, in Ref. 23 , authors devised a novel distance measure along with detail proof of its required properties.…”

Section: Introductionmentioning

confidence: 99%

Cosine similarity measures between q-rung orthopair linguistic sets and their application to group decision making problems

Ali

Naeem

2022

Sci Rep

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The q-rung orthopair linguistic set (q-ROLS), a combined version of linguistic term sets and q-rung orthopair fuzzy set, is an efficient mathematical tool to accomplish the imprecise information while solving the decision-making problems. Under this environment, we propose additional operations and relations to deal with the decision information, and some properties are well proved. Furthermore, we propound some cosine similarity measures and weighted cosine similarity measures for q-ROLSs based on the traditional cosine similarity measures with a brief study of related properties. In the proposed similarity measures, various linguistic scale functions are utilized in order to take into account the semantics of linguistic terms. Besides this, we employ the stated q-rung orthopair linguistic similarity measures to multi-criteria group decision making problems, in which the weights of DMs are delineated by the projection of individual decisions on the ideal decision results. At last, a numerical example is used to demonstrate the practicality of the suggested technique, and its efficacy is validated by comparison with prevailing techniques. The suggested method’s sensitivity and stability analyses are also provided.

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“…In order to enhance the quality of q-ROFS, so it can deal with vagueness and impreciseness, Li et al [10] proposed qrung picture fuzzy set (q-RPFS), which takes the advantages of both q-ROFS and PFS. To effectively aggregate q-RPF data, some aggregation operators have been developed [11]- [16]. In [11], the authors proposed the q-rung picture linguistic weighted Heronian mean (q-RPLWHM) and the q-rung picture linguistic geometric Heronian mean (q-RPLGHM) operators.…”

Section: Introductionmentioning

confidence: 99%

“…Yang et al, [15] presented the interval q-RPF Heronian mean (IVq-RPtFHM) operators based on the new operational laws of the IVq-RPtF numbers. Pinar and Boran [16] introduced a novel distance measure for q-RPFS. The proposed distance measure is used in q-RPF ELECTRE integrated with TOPSIS method.…”

Section: Introductionmentioning

confidence: 99%

A New Multi Attribute Decision Making Method Based on the T-Spherical Hesitant Fuzzy Sets

Al-Quran

2021

IEEE Access

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In this paper, we first introduce the concept of T-spherical hesitant fuzzy set (T-SHFS) on the basis of the combination of T-spherical fuzzy sets(T-SFSs) and hesitant fuzzy sets (HFSs). This model can provide more accuracy in expressing fuzzy and indeterminate data. Then, we develop the basic operational laws of T-SHFSs and study their properties. Also, we propose the T-spherical hesitant fuzzy weighted averaging (T-SHFWA) operator and the T-spherical hesitant fuzzy weighted geometric (T-SHFWG) operatorand investigate their properties. Furthermore, two newly approaches to multi attribute decision making within the framework of T-SHFS are developed on the basis of the proposed aggregation operators. An illustrative example is given to demonstrate the effectiveness of the developed approaches in dealing with uncertain and indeterminate decision making problems. Finally, the proposed models' performance is evaluated to the existing models. Results from this comparison analysis reveal a great similarity and consistency while using other models.

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A novel distance measure on q-rung picture fuzzy sets and its application to decision making and classification problems

Cited by 31 publications

References 39 publications

Spherical Linear Diophantine Fuzzy TOPSIS Algorithm for Green Supply Chain Management System

Spherical Linear Diophantine Fuzzy TOPSIS Algorithm for Green Supply Chain Management System

Cosine similarity measures between q-rung orthopair linguistic sets and their application to group decision making problems

A New Multi Attribute Decision Making Method Based on the T-Spherical Hesitant Fuzzy Sets

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