首页> 外文OA文献 >Verifikasi Model Arima Musiman Menggunakan Peta Kendali Moving Range (Studi Kasus : Kecepatan Rata-rata Angin di Badan Meteorologi Klimatologi dan Geofisika Stasiun Meteorologi Maritim Semarang)
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Verifikasi Model Arima Musiman Menggunakan Peta Kendali Moving Range (Studi Kasus : Kecepatan Rata-rata Angin di Badan Meteorologi Klimatologi dan Geofisika Stasiun Meteorologi Maritim Semarang)

机译:使用全程移动地图验证季节性Arima模型(案例研究:气象气候和地球物理站三宝垄海洋气象站的平均风速)

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摘要

Forecasting method Box-Jenkins ARIMA (Autoregressive Integrated Moving Average) is a forecasting method that can provide a more accurate forecasting results. To verify the model obtained using the one Moving Range Chart. The control charts are used to determine the change in the pattern of file seen from the residual value (the difference between the actual file and the file forecasting). File used in this study the average wind speed in the Tanjung Emas harbor during January 2008 to December 2013. The best of Seasonal ARIMA model is ARIMA (0,0,1) (0,0,1) 12. The results of the verification using the Moving Range Control Chart on the model showed that all residual values are within control limits to the length of the shortest interval, means of verification results show that the model is a good model used for forecasting future periods. Forecasting is generated during the period of the next 15 shows the seasonal pattern. This is shown in the figure forecast 2014 average wind speeds are highest in January, as well as forecasting the 2015 figures the average speed of the highest winds also occurred in January. Forecasting results reflect past file, because the actual file used also showed a seasonal pattern with the same seasonal period is annual, where the numbers mean wind speeds are highest in January.
机译:预测方法Box-Jenkins ARIMA(自回归综合移动平均线)是一种可以提供更准确的预测结果的预测方法。验证使用一张移动范围图获得的模型。控制图用于确定从残差值(实际文件与文件预测之间的差异)来看文件格式的变化。本研究中使用的文件是2008年1月至2013年12月丹绒埃马斯海港的平均风速。季节性ARIMA模型的最佳选择是ARIMA(0,0,1)(0,0,1)12.验证结果使用模型上的“移动范围控制图”显示,所有残差值均在最短间隔长度的控制范围内,验证结果表明,该模型是用于预测未来期间的良好模型。预测是在接下来的15个时段内生成的季节性模式。从预测2014年1月最高风速的数字以及预测2015年1月最高风速的平均速度的数据中可以看出这一点。预测结果反映了过去的文件,因为实际使用的文件还显示了一个季节性模式,同一季节是每年一次,该数字表示一月份的风速最高。

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