HESITANT FUZZY INFORMATION MEASURES DERIVED FROM T-NORMS an‎d S-NORMS

In this contribution, we rst introduce the concept of metrical T-norm-based similarity measure for hesitant fuzzy sets (HFSs) by using the concept of T-norm-based distance measure. Then, the relationship of the proposed metrical T-norm-based similarity measures with the other kind of information measure, called the metrical T-norm-based entropy measure is discussed. The main feature of the proposed metrical T-norm-based similar- ity measures is a possibility of comparing similarity between HFSs without regarding what value is returned by the similarity measure. To illustrate the application of the proposed metrical T-norm-based similarity measures, we consider two problems of medical diagnosis and pattern recognition to com- pare the proposed metrical T-norm-based similarity measures with a number of the existing HFS similarity measures.