  For a certain moment, the information volume represented in a probability
space can be accurately measured by Shannon entropy. But in real life, the
results of things usually change over time, and the prediction of the
information volume contained in the future is still an open question. Deng
entropy proposed by Deng in recent years is widely applied on measuring the
uncertainty, but its physical explanation is controversial. In this paper, we
give Deng entropy a new explanation based on the fractal idea, and proposed its
generalization called time fractal-based (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), can express more uncertain information than all of existing
methods.
