论文部分内容阅读
将灰色系统预测模型GM(1,1)与马尔柯夫链相结合,建立玉林市早稻产量预测模型。应用结果表明:(1)模型具有灰色微分动态模型的特点,反映了产量变化的灰色过程;(2)应用马尔柯夫链对该模型所产生的误差进行修正,克服了GM模型误差较大等缺点,大大提高了预测精度,(3)灰色系统理论与随机过程理论相结合,互相取长补短,为统计理论发展开创了新的路径,也为产量预测预报提供了新的方法。
Combining the gray system prediction model GM (1,1) with Markov chain, the prediction model of early rice yield in Yulin was established. The application results show that: (1) The model has the characteristics of gray differential dynamic model, which reflects the gray process of output changes; (2) The error generated by the model is corrected by using Markov chain, which overcomes the shortcomings such as large error of GM model, Which greatly improves the prediction accuracy. (3) The combination of gray system theory and stochastic process theory, complement each other, create a new path for the development of statistical theory and also provide a new method for forecasting yield.