An improved information volume of mass function based on plausibility transformation method

Abstract

The information volume of mass function (IVMF) is an effective tool for measuring the uncertainty of basic probability assignments in power sets. However, the current IVMF will yield counterintuitive results when applied to an inconsistent frame of discernment (FOD). To address this issue, an improved IVMF based on plausibility transformation method (PTM) is proposed in this paper. Compared to existing methods, the proposed method yields a more reasonable result in cases where the FOD is inconsistent. Additionally, the proposed IVMF can be viewed as a geometric mean of first-order information volume and higher-order information volume, which can degenerate into Shannon Entropy in a probability distribution. The efficacy and rationality of the proposed IVMF are demonstrated through a series of numerical examples and an application in threat assessment.