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本文在分别运用灰色数列GM(1,1)模型和一阶自回归模型对我市尘肺发病趋势进行预测的基础上,利用加权综合预测法对这两种定量预测方法的预测结果进行加权合并。由于它充分考虑了GM(1,1)模型及自回归模型所获结果的权重,取两种方法之所长,因此,可减少预测误差,提高预测的准确性。结果表明,加权综合预测法较任何单一预测方法的预测效果都好,且计算简便。提示,该法是一种值得进一步推广试用的尘肺发病趋势预测方法。
In this paper, we forecast the trend of pneumoconiosis in our city by using the GM (1,1) model and the first-order autoregressive model respectively, and use the weighted synthetic forecasting method to weigh and combine the forecast results of these two quantitative forecasting methods. Because it takes full account of the weights of the results obtained from the GM (1,1) model and the autoregressive model, taking the strengths of the two methods, it can reduce the prediction error and improve the accuracy of the prediction. The results show that the weighted synthetic forecasting method is better than any single forecasting method and the calculation is simple. Tip, the method is a worthwhile to promote the trial of pneumoconiosis trend forecasting method.