Higher order information volume of mass function


METADATA ONLY
Loading...

Date

2022-03

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

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.

Permanent link

Publication status

published

Editor

Book title

Volume

586

Pages / Article No.

501 - 513

Publisher

Elsevier

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Dempster-Shafer evidence theory; Time fractal-based belief entropy; Information volume; Mass function; Time splitting; Generalized Deng entropy

Organisational unit

Notes

Funding

Related publications and datasets