The Improvement And Application Of The Grey Markov Chain

A scientific, accurate and effective prediction model not only is beneficial to study thing-in-itself, but also provide important references for the formulation of the corresponding decisions reasonably. In recent years, Grey Markov chain model study China’s consumer price index effectively. This paper put forward an improved model not only overcomes the deficiency that the state spaces of the original Grey Markov chain model are divided based on experience,but also improve the efficiency of the divided spaces are not guaranteed to pass the Markov property test. The results confirm that, compared with other popular models, the proposed Grey Markov forecasting model improves the predictions of China’s consumer price index, which indicates that the developed hybrid method exhibits stronger forecasting ability.