Research on the Economic Data Model of Hidden Markov Chain

Abstract

Markov chain is widely used in the fields of natural science and engineering technology because of its no aftereffect. The classic Markov chain does not reflect the uncertainty of the object state, and when the state division boundary is too clear, the state transition is unstable. In order to maintain the stability of the state transition and be able to effectively represent and deal with the uncertainty of the object state for sex, this paper proposes a reliability Markov model. The new model introduces the Dempster-Shafer (DS) evidence theory to describe the uncertainty of the object state, classifies all the object states into an identification framework, establishes a basic probability assignment function, and then generates a proposition transition probability matrix, and finally according to the object The current state gets the future state. The reliability Markov model proposed in this paper is a generalization of the classic Markov chain, which is backward compatible with its properties. The example shows that the new model overcomes the above-mentioned shortcomings, and obtains more reasonable and accurate results than the classic Markov chain, and has higher effectiveness and practicability.