An Approach to Rank Picture Fuzzy Numbers for Decision Making Problems

Si, Amalendu; Das, Sujit; Kar, Samarjit

doi:10.31181/dmame1902049s

Cited by 52 publications

(34 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Khan et al [12] define the generalized picture fuzzy soft set and applied them to decision-making problems. For study more about decision making, we refer to [13][14][15][16][17][18][19].Yager [20,21] defines the Pythagorean fuzzy sets P yF S, which is the successful extension of intuitionistic fuzzy sets, by putting a new condition on positive membership ξ and negative membership functions ν, i.e., 0 ≤ ξ 2 + ν 2 ≤ 1. This new condition expand the domain of membership functions like if we have ξ = 0.7 and ν = 0.5, then we cannot deal it with intuitionistic fuzzy set because 0.7 + 0.5 ≥ 1 but 0.7 2 + 0.5 2 = 0.49 + 0.25 = 0.74 ≤ 1 and hence P yF S applied successfully.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Distance and Similarity Measures for Spherical Fuzzy Sets and Their Applications in Selecting Mega Projects

et al. 2020

View full text Add to dashboard Cite

A new condition on positive membership, neutral membership, and negative membership functions give us the successful extension of picture fuzzy set and Pythagorean fuzzy set and called spherical fuzzy sets ( SFS ) . This extends the domain of positive membership, neutral membership, and negative membership functions. Keeping in mind the importance of similarity measure and application in data mining, medical diagnosis, decision making, and pattern recognition, several studies on similarity measures have been proposed in the literature. Some of those, however, cannot satisfy the axioms of similarity and provide counter-intuitive cases. In this paper, we proposed the set-theoretic similarity and distance measures. We provide some counterexamples for already proposed similarity measures in the literature and shows that how our proposed method is important and applicable to the pattern recognition problems. In the end, we provide an application of a proposed similarity measure for selecting mega projects in under developed countries.

show abstract

mentioning

confidence: 99%

“…Khan et al [12] define the generalized picture fuzzy soft set and applied them to decision-making problems. For study more about decision making, we refer to [13][14][15][16][17][18][19].…”

mentioning

confidence: 99%

Distance and Similarity Measures for Spherical Fuzzy Sets and Their Applications in Selecting Mega Projects

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Picture fuzzy sets give three membership degrees of an element named the positive membership degree, the neutral membership degree, and the negative membership degree, respectively. The picture fuzzy set solved the voting problem successfully, and is applied to clustering [ 26 ], fuzzy inference [ 27 ], and decision-making [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Spherical Fuzzy Logarithmic Aggregation Operators Based on Entropy and Their Application in Decision Support Systems

Jin

Ashraf

Abdullah

2019

Entropy

View full text Add to dashboard Cite

Keeping in view the importance of new defined and well growing spherical fuzzy sets, in this study, we proposed a novel method to handle the spherical fuzzy multi-criteria group decision-making (MCGDM) problems. Firstly, we presented some novel logarithmic operations of spherical fuzzy sets (SFSs). Then, we proposed series of novel logarithmic operators, namely spherical fuzzy weighted average operators and spherical fuzzy weighted geometric operators. We proposed the spherical fuzzy entropy to find the unknown weights information of the criteria. We study some of its desirable properties such as idempotency, boundary and monotonicity in detail. Finally, the detailed steps for the spherical fuzzy decision-making problems were developed, and a practical case was given to check the created approach and to illustrate its validity and superiority. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our proposed method. Results indicate that the proposed method is suitable and effective for the decision process to evaluate their best alternative.

show abstract

“…For example, Ibrahim Badi & Pamucar [1] proposed a method to implement a hybrid Grey theory-MARCOS method for decisionmaking regarding the selection of suppliers in the Libyan Iron and Steel Company (LISCO) to help it compete. Si et al [2] propose a new method to calculate the score to rank the PFNs using positive ideal solution, negative ideal solution and average neutral value of the alternatives. Neutral degree of PFS has an active role in our proposal.…”

Section: Introductionmentioning

confidence: 99%

Method of Group Decision Making with Interval Grey Numbers based on Grey Correlation and Relative Close Degree

Liú

Ding

et al. 2020

Teh. vjesn.

View full text Add to dashboard Cite

With the development of society, big data's concept is mentioned more and more. However, in the numerous and complex mass data, the effective information is often very limited, and the data often show the complex characteristics of "close and orderly short-term correlation and large long-term disturbance", which is difficult to be expressed by a long sequence composed of a single real value. This paper takes the interval grey number as the research object for the uncertain system of "less data and poor information". According to the multi-attribute group decisions problem with attribute's values of interval grey number and the weights of decision-makers and attributes that are completely unknown, a method of group decision making with interval grey numbers based on grey correlation and relative close degree is proposed. For the purpose of making effective decisions, the weights of decision-makers and attributes are calculated by correlation degree of decision information which is measured by the model of grey correlation analysis based on interval grey number deviation degree. On this basis, the correlation degree between the scheme and the positive and negative ideal schemes are computed, and then the grey correlation and relative close degree of the scheme is calculated. Finally, the scheme is sorted according to the value of the grey correlation and relative close degree. The rationality and feasibility of the proposed method are verified by numerical examples.

show abstract

An Approach to Rank Picture Fuzzy Numbers for Decision Making Problems

Cited by 52 publications

References 0 publications

Distance and Similarity Measures for Spherical Fuzzy Sets and Their Applications in Selecting Mega Projects

Distance and Similarity Measures for Spherical Fuzzy Sets and Their Applications in Selecting Mega Projects

Spherical Fuzzy Logarithmic Aggregation Operators Based on Entropy and Their Application in Decision Support Systems

Method of Group Decision Making with Interval Grey Numbers based on Grey Correlation and Relative Close Degree

Contact Info

Product

Resources

About