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

摘要：

　　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.

关键词： Markov Process Quadratic Function Parameter Joint Model Prediction

作者: Dewang Li Meilan Qiu

作者单位: School of Mathematics and Statistics,Yunnan University,Kunming Yunnan 650091,China;Department of Mat Faculty of Science,Xian Jiaotong University,Xian Shanxi 710049,China

会议类型: 国际会议

会议名称: the 2012 International Conference on Manufacturing Engineering and Automation (2012年制造工程与自动化国际会议(ICMEA2012))

会议地点: 广州

会议语种:英文

页码: 2509-2512

在线出版日期: 2012-11-16（万方平台首次上网日期，不代表论文的发表时间）