ER-IVMF: Evidential Reasoning Based on Information Volume of Mass Function

Abstract

Evidential reasoning (ER) under uncertainty is essential for various applications such as classification, prediction, and clustering. The effective realization of ER is still an open issue. Reliability plays a decisive role in the final performance as a major parameter of ER, reflecting the evidence’s inner information. This paper proposed ER based on the information volume of the mass function (ER-IVMF), which considers both weight and reliability. Numerical examples were designed to illustrate the effectiveness of the ER-IVMF. Additionally, a sports scoring system experiment was conducted to validate the superiority of the ER-IVMF. Considering the reliability based on high-order evidence information, the output of the proposed method was more accurate than that of the other methods. The experimental results proved that the proposed method was practical for addressing sports-scoring problems.