Using Parameter Joint Model to Predict the Grain Yield of Guangxi Province

Abstract

The principle of the Markov chain model is described in this paper, based on the combination forecasting thought and Markov chain thinking, we combine joint forecasting model with the state of the Markov chain transfer model , which is better reflected the law of development of the system of things. We get with parameters in the joint model, and use the joint model to predict the Guangxi food production. Based on historical grain yields data from 1964 to 2011 and the nature of the growth curve regression equation, we establish parameter joint prediction model of Markov and the quadratic function growth curve, which can predict the future grain production of Guangxi province, and we could proof its feasibility. The accuracy of parameter joint model prediction is high, which can be validated by historical grain yields data.