文章摘要
乔松珊,张建军.加权马尔可夫链理论在肉类产量预测中的应用[J].广东农业科学,2013,40(15):218-220
加权马尔可夫链理论在肉类产量预测中的应用
Application of weighted Markov theory in meat yield prediction
  
DOI:
中文关键词: 加权马尔可夫链理论  残差修正  肉类产量  预测精度
英文关键词: weighted Markov theory  residual error correction  meat yield  forecasting accuracy
基金项目:
作者单位
乔松珊,张建军 1.中原工学院信息商务学院河南郑州4500072.河南农业大学信息与管理科学学院河南郑州450002 
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中文摘要:
      为准确反映肉类产量的波动特征,基于加权马尔可夫链理论提出了灰色残差修正模型,采用均值-均方差分级法,将残差灰拟合精度指标划分为4个状态,利用加权马尔可夫链理论对残差预测值进行修正。以1994要2011 年郑州市肉类产量为基础,建立预测模型进行实证分析,并在模型中加入等维信息,结果表明,与传统的灰色预测相比,预测平均相对误差由21.88%降低为1.312%,较好地提高了预测精度。
英文摘要:
      In order to reflect the fluctuation characteristics of meat production, we proposed the grey residual improved model based on the weighted Markov theory. Grey precision index of residual was classified into 4 states by using mean -standard deviation classification method, the forecasting value of residual was modified based on the weighted Markov theory. The weighted Markov improved model was formed based on the meat yield from 1994 to 2011 in Zhengzhou with adding the dimension information in the model. The results showed that compared to the traditional grey prediction, the average relative prediction error was reduced from 21.88% to 1.31%.
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