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Study and Application of Grain Yield Forecasting Model

机译:粮食产量预测模型的研究与应用

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There are some poor accuracy problems of grain yield prediction. GM (1, 1) prediction model and ARIMA (1,1,1) prediction model were established according to Jilin Province 1998-2011 grain yield data. In the same training sample, 2 kinds of methods were used to forecast grain yield. The average error is 7.88% and 12.32%, the average precision accuracy is 92.12%and 87.68% respectively. The test results show that the average prediction accuracy of grey system is higher than that of the time sequence model, and it can be applied to the prediction of grain yield.
机译:谷物产量预测有一些差的准确性问题。根据吉林省1998-2011粮食产量数据建立了GM(1,1)预测模型和Arima(1,1,1)预测模型。在相同的训练样品中,使用2种方法来预测谷物产量。平均误差分别为7.88%和12.32%,平均精度精度分别为92.12%和87.68%。测试结果表明,灰色系统的平均预测精度高于时间序列模型的平均预测精度,并且可以应用于谷物产量的预测。

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