摘要： 采用最优加权方法, 建立了基于灰色预测模型、灰色马尔科夫预测模型及逻辑斯蒂预测模型的组合模型;并根据东北地区1949-2008年粮食产量资料, 利用组合模型预测了该地区未来10年的粮食产量。结果得到, 灰色预测、马尔科夫预测、逻辑斯蒂预测和组合预测方法的预测粮食产量的平均相对百分误差分别为:12.74%, 3.02%, 13.29%, 2.87%, 结果证明组合预测模型可以较好地提高粮食产量的预测精度。通过组合模型预测结果表明, 到2015年东北地区的粮食产量可以达到1.25亿t, 可以完成该地区增产150亿kg粮食的任务, 到2018年, 粮食产量预计可达1.38亿t, 东北地区增粮潜力巨大。
关键词:
组合预测模型,
最优加权法,
粮食产量
Abstract: This paper built the combinatorial predicting model of grey predicting model, grey markova transition matrix model, logistic predicting model by the optimal weighted method. The coupling model was also applied to predict the food production of northeaster China in the next ten years, based on the food production data from year 1949 to 2008. The studied results showed that the mean relative errors of predicted food production of grey predicting model, grey-markova transition matrix model, logistic predicting model, combinatorial predicting model were 12.74%, 3.02%, 13.29%, 2. 87%, The combinatorial predicting model could improve the precision of predicting food production. The food production of northeaster China will arrive at 0. 125 billion and 0. 138 billion ton in year of 2015 and 2018, predicted by combinatorial predicting model, which could finish the task increasing 30 million ton food and showed great potential of increasing food production.
Key words:
Combinatorial predicting model,
Optimal weighted method,
Food production
中图分类号:
YAO Zuo-fang, LIU Xing-tu, YANG Fei, YAN Min-hua, SUN Li, LU Xin-rui. The Combinatorial Predicting Model of the Grain Yields in the Northeast of China[J]. ACTA AGRICULTURAE BOREALI-SINICA, doi: 10.7668/hbnxb.2009.S2.048.