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Predictive Efficiency Comparison of ARIMA-time-series and the Grey System GM(1,1) Forecast Model on Forecasting the Incidence Rate of Hepatitis B

机译:ARIMA - 时序和灰色系统GM(1,1)预测预测乙型肝炎发生率预测模型的预测效率比较

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To compare the stochastic autoregressive integrated moving average (ARIMA) model and the grey system GM(1,1) model to predict the hepatitis B incidence in Qian'an. Considering the Box-Jenkins modeling and GM(1,1) model approach, hepatitis B incidence was collected monthly from 2004 to 2011, a SARIMA model and a gray system GM(1,1) model were fit. Then, these models were used for calculating hepatitis B incidence for the last 6 observations compared with observed data. The constructed models were performed to predict the monthly incidence rate in 2013. The model SARIMA(0,1,1)(0,1,1)_(12) and was established finally and the residual sequence was a white noise sequence. Using Excel 2003 to establish the gray system GM(1,1) model of hepatitis B incidence and evaluating the accuracy of the mode as well as forecasting. By posterior-error-test (C=0.435, p=0.821) and residual test, the model accuracy was qualified. It was necessary and practical to apply the approach of ARIMA model in fitting time series to predict hepatitis within a short lead time. The prediction results showed that the hepatitis B incidence in 2013 had a slight upward trend.
机译:比较随机归共综合移动平均(ARIMA)模型和灰色系统GM(1,1)模型来预测黔南的乙型肝炎发病率。考虑到盒子jenkins建模和gm(1,1)模型方法,从2004年到2011年收集乙型肝炎发病率,Sarima模型和灰色系统GM(1,1)模型适合。然后,与观察到的数据相比,这些模型用于计算过去6个观察的乙型肝炎的发生率。进行了构建的模型以预测2013年的月度发生率。模型Sarima(0,1,1)(0.1,1)_(12),最终成立,残留序列是白色噪声序列。使用Excel 2003建立灰色系统GM(1,1)模型的乙型肝炎发病率,并评估模式的准确性以及预测。通过后误差测试(C = 0.435,P = 0.821)和残留测试,模型精度是合格的。在合适的时间序列中应用Arima模型的方法是必要的,实际的是,在短时间内预测肝炎。预测结果表明,2013年的乙型肝炎发病率略有上升趋势。

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