A novel similarity measure between picture fuzzy sets based on transformation techniques and its applications in mobile multimedia healthcare

With the development of mobile multimedia devices, mobile multimedia based mobile health healthcare has become a popular style. However, multimedia mobile health healthcare is not an easy task as it involves human decision making which is imprecise, vague and uncertain. To handle the uncertainty of information, picture fuzzy sets (PFSs) is a good choice. As one of the important topics in PFSs, the similarity measure between PFS has been assessed by several studies within the literature. Most existing measures of PFSs, however, cannot completely meet the properties of similarity measures in some special cases. In this paper, on the basic of the transformed right-angled triangular-based pyramids, a novel similarity measure is developed to handle pattern recognition problems. First, we originally present the conversion techniques between picture fuzzy numbers (PFNs) and their corresponding right-angled triangular-based pyramids fuzzy numbers. Then, we establish a new similarity measure for PFNs on the basic of the barycenter points of the corresponding right-angled triangular-based pyramids transformed from PFNs. Moreover, a comparison of different algorithms as regards PFSs and Neutrosophic sets (NSs) is performed to test performance of the established similarity measure within picture fuzzy environment. Finally, a new proposed TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is used to identifying the ranking order of the determinants of adoption of mobile multimedia healthcare services for the aged. The findings indicate that the established algorithm can fully fulfill the conditions of similarity measure, produce more reasonable and creditable results, and perform well in complex situations.