Multicriteria Decision-making Method using Cosine Similarity Measures for Reduct Fuzzy Sets of Interval-valued Fuzzy Sets

2014 ◽  
Vol 9 (1) ◽  
Author(s):  
Shapu Ren ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Similarity Measures ◽  
Multicriteria Decision Making ◽  
Cosine Similarity ◽  
Multicriteria Decision ◽  
Cosine Similarity Measures ◽  
Interval Valued

scholarly journals Some Similarity and Distance Measures between Complex Interval-Valued q-Rung Orthopair Fuzzy Sets Based on Cosine Function and their Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Sultan Aljahdali
Keyword(s):  
Decision Making ◽  
Solution Method ◽  
Similarity Measures ◽  
Cosine Similarity ◽  
Distance Measures ◽  
Uncertain Information ◽  
Cosine Similarity Measures ◽  
Complex Valued ◽  
Interval Valued ◽  
The Ideal

The purpose of this paper is to present a new method to solve the decision-making algorithm based on the cosine similarity and distance measures by utilizing the uncertain and vague information. A complex interval-valued q-rung orthopair fuzzy set (CIVQROFS) is a reliable and competent technique for handling the uncertain information with the help of the complex-valued membership grades. To address the degree of discrimination between the pairs of the sets, cosine similarity measures (CSMs) and distance measures (DMs) are an accomplished technique. Driven by these, in this manuscript, we defined some CSMs and DMs for the pairs of CIVQROFSs and investigated their several properties. Choosing that the CSMs do not justify the axiom of the similarity measure (SM), then we investigate a technique to developing other CIVQROFSs-based SMs using the explored CSMs and Euclidean DMs, and it fulfills the axiom of the SMs. In addition, we find the cosine DMs (CDMs) by considering the inter-relationship between the SM and DMs; then, we have modified the procedure for the rank of partiality by similarity to the ideal solution method for the CDMs under investigation, which can deal with the associated decision-making problems not only individually from the argument of the opinion of geometry but also the fact of the opinion of algebra. Finally, we provide a numerical example to demonstrate the practicality and effectiveness of the proposed procedure, which is also in line with existing procedures. Graphical representations of the measures developed are also used in this manuscript.

scholarly journals An Exhaustive Study of Possibility Measures of Interval-Valued Intuitionistic Fuzzy Sets and Application to Multicriteria Decision Making

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Fatma Dammak ◽  
Leila Baccour ◽  
Adel M. Alimi
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multicriteria Decision Making ◽  
Possibility Theory ◽  
Intuitionistic Fuzzy Sets ◽  
Decision Matrix ◽  
Multicriteria Decision ◽  
Intuitionistic Fuzzy ◽  
Exhaustive Study ◽  
Interval Valued

This work is interested in showing the importance of possibility theory in multicriteria decision making (MCDM). Thus, we apply some possibility measures from literature to the MCDM method using interval-valued intuitionistic fuzzy sets (IVIFSs). These measures are applied to a decision matrix after being transformed with aggregation operators. The results are compared between each other and concluding remarks are drawn.

Selection of an alternative based on interval-valued hesitant picture fuzzy sets

2021 ◽  
pp. 1-11
Author(s):  
Tabasam Rashid ◽  
M. Sarwar Sindhu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Criteria Decision Making ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets ◽  
Ambiguous Information ◽  
Cosine Similarity Measures ◽  
Picture Fuzzy Sets ◽  
Interval Valued ◽  
Selection Of

Motivated by interval-valued hesitant fuzzy sets (IVHFSs) and picture fuzzy sets (PcFSs), a notion of interval-valued hesitant picture fuzzy sets (IVHPcFSs) is presented in this article. The concept of IVHPcFSs is put forward and some operational rules are developed to deal with it. The cosine similarity measures (SMs) are modified for IVHPcFSs to deal with interval-valued hesitant picture fuzzy (IVHPcF) data and the linear programming (LP) methodology is used to find out the criteria’s weights. A multiple criteria decision making (MCDM) approach is then developed to tackle the vague and ambiguous information involved in MCDM problems under the framework of IVHPcFSs. For the validation and strengthen of the proposed MCDM approach a practical example is put forward to select the educational expert at the end.

scholarly journals SIMILARITY MEASURES OF PYTHAGOREAN FUZZY SETS WITH APPLICATIONS TO PATTERN RECOGNITION AND MULTICRITERIA DECISION MAKING WITH PYTHAGOREAN TOPSIS

2021 ◽  
Author(s):  
Zahid Hussain
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Sets ◽  
Similarity Measures ◽  
Multicriteria Decision Making ◽  
Linguistic Variables ◽  
Multicriteria Decision ◽  
Pythagorean Fuzzy Sets ◽  
Rényi Divergence

The construction of divergence measures between two Pythagorean fuzzy sets (PFSs) is significant as it has a variety of applications in different areas such as multicriteria decision making, pattern recognition and image processing. The main purpose of this study to introduce an information-theoretic divergence so-called Pythagorean fuzzy Jensen-Rényi divergence (PFJRD) between two PFSs. The strength and characterization of the proposed Jensen-Rényi divergence between Pythagorean fuzzy sets lie in its practical applications which are very closed to real life. The proposed divergence measure is utilized to induce some useful similarity measures between PFSs. We apply them in pattern recognition, characterization of the similarity between linguistic variables and in multiple criteria decision making. To demonstrate the practical utility and applicability, we present some numerical examples related to daily life with the construction of Pythagorean fuzzy TOPSIS (Techniques of preference similar to ideal solution). Which is utilized to rank the Belt and Road initiative (BRI) projects. Our numerical simulation results show that the suggested measures are well suitable in pattern recognition, characterization of linguistic variables and multi-criteria decision-making environment.

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