Exponential Function-Based Similarity Measures for q-Rung Linear Diophantine Fuzzy Sets and Their Application to Clustering Problem

The q-rung linear Diophantine fuzzy set is a recently developed tool to handle with uncertain and awkward information in real-life issues applicable where reference parameter-based opinions. Similarity measures are distance dimensions representing features of the objects. Keeping advantages above analysis, this paper proposes similarity based on exponential function for sets thus presents first formulas calculating coefficient between two sets. These proposed applied clustering problem results analyzed. In addition, comparison outputs new discussed ensure their good performance.