Similarity measures of intuitionistic fuzzy sets based on cosine function for the decision making of mechanical design schemes
Jun Ye
Abstract
Jun Ye
Abstract
Based on cosine function and the information carried by the membership degrees, nonmembership degree and hesitancy degree in intuitionistic fuzzy sets (IFSs), this paper proposes two new cosine similarity measures and weighted cosine similarity measures between IFSs. Then, we give the comparative analysis of various trigonometric similarity measures by several numerical examples to illustrate the effectiveness of the developed cosine similarity measures of IFSs. Furthermore, we develop a decision-making method using the weighted cosine similarity measures for choosing mechanical design schemes (alternatives). Finally, a decision-making example on choosing mechanical design schemes is given to demonstrate the applications and efficiency of the proposed decision-making method.
OpenAlex reports 84 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Based on cosine function and the information carried by the membership degrees, nonmembership degree and hesitancy degree in intuitionistic fuzzy sets (IFSs), this paper proposes two new cosine similarity measures and weighted cosine similarity measures between IFSs. Then, we give the comparative analysis of various trigonometric similarity measures by several numerical examples to illustrate the effectiveness of the developed cosine similarity measures of IFSs. Furthermore, we develop a decision-making method using the weighted cosine similarity measures for choosing mechanical design schemes (alternatives). Finally, a decision-making example on choosing mechanical design schemes is given to demonstrate the applications and efficiency of the proposed decision-making method.
Key concepts: Cosine similarity, Trigonometric functions, Similarity (geometry), Trigonometry, Mathematics, Fuzzy logic, Function (biology), Membership function