Improved Grey Markov Combination Forecasting Model And Its Application

The paper based on Grey Markov Forecasting Model as the research theme,in combination with gray system theory and the theory of Markov chains,and the idea of metabolism and weight are blended in Grey Markov Forecasting Model,to improve the Grey Markov Forecasting Model,and made an data analysis.The Grey Forecasting Model based on less information as the main research theme,simple of theory,ease of calculation,the Model for less information has better prediction accuracy.The Markov Forecasting Model suitable for those who predict a large data fluctuations in stochastic processes,the model required an object of Markov prediction.Firstly,the combination of the Grey Forecasting Model and Markov Forecasting Mode form the Grey Markov Forecasting Model,the Grey Forecasting Model predicted the general trend of the data sequence,and no the basis of data on trends in processing,the paper applied to the Markov Forecasting Model,hope to play theiradvantages,achieve a goal of improve prediction accuracy.But the result is not ideal by example.So this paper proposes a weighted method based on the Genetic Algorithm,improved Grey Markov Forecasting Model,A weighted Grey Markov forecasting Model is established on the basis of metabolism.And analyzed by an example.The case study shows that this paper used the before and after the Grey Markov Forecasting Model to predict the rainfall,the results are related to the state of the original data partition.Under the same state,the improved model has a better forecast effect.