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

机译:用参数联合模型预测广西省粮食产量

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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.
机译:本文描述了马尔可夫链模型的原理,在结合预测思想和马尔可夫链思想的基础上,将联合预测模型与马尔可夫链转移模型的状态相结合,较好地反映了系统的发展规律。在联合模型中获取参数,并用联合模型预测广西粮食产量。基于1964年至2011年的历史粮食单产数据和增长曲线回归方程的性质,建立参数联合预测模型。马尔可夫方程和二次函数增长曲线可以预测广西省未来的粮食产量,并证明其可行性。参数联合模型预测的准确性很高,可以通过历史粮食单产数据加以验证。

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