Higher order information volume of mass function

• Published in: Information sciences Vol. 586; pp. 501 - 513
• Main Authors: Zhou, Qianli, Deng, Yong
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.03.2022
• Subjects: Dempster-Shafer evidence theory; Generalized Deng entropy; Information volume; Mass function; Time fractal-based belief entropy; Time splitting; Generalized Deng entropy; Dempster-Shafer evidence theory; Information volume; Mass function; Time splitting; Time fractal-based belief entropy
• ISSN: 0020-0255; 1872-6291
• DOI: 10.1016/j.ins.2021.12.005

For a certain moment, the information volume of probability space can be accurately expressed by Shannon entropy. But in real life, the distribution of events usually change over time, and the prediction of the information volume for a period of time in the future is still an open question. Deng entropy proposed in recent years is widely applied on measuring the uncertainty, but it is controversial because of its physical explanation and counter-intuitive results. In this paper, we give Deng entropy a new explanation based on the fractal idea, and propose its generalization called time fractal-based belief (TFB) entropy. The TFB entropy is recognized as predicting the uncertainty over a period of time by splitting times, and its maximum value, called higher order information volume of mass function (HOIVMF), which can express the information for a period time reasonably.