A Type of Score Function on Intuitionistic Fuzzy Sets with Double Parameters and Its application to Pattern Recognition and Medical Diagnosis

Abstract

In this paper, we first present a novel intuitionistic fuzzy set with double parameters (IFSDP). Compared with intuitionistic fuzzy sets (IFS), IFSDP can provide membership function with parameters, non-membership function with parameters, and hesitancy function with parameters. Based on IFS and IFSDP, we propose a type of score function, which is more effective than conventional distance measure method and similarity measure method by a pattern recognition example. Finally, based on the score function of IFSDP, a pattern recognition example applied to medical diagnosis is given to illustrate the application of IFSDP and its score. The simulation results show that the method of IFSDP is more comprehensive and flexible than the traditional IFS method.

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