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Forecasting Monthly Precipitation in Sylhet City Using ARIMA Model

机译:用ARIMA模型预测锡尔赫特市的月降水量

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In this study a seasonal ARIMA model was built using Box and Jenkins method to forecast long term rainfall in Sylhet. For this purpose rainfall data from 1980 to 2010 of Sylhet station were used to build and check the model. Rainfall data from 1980 to 2006 were used to develop the model while data from 2007 to 2010 were used to verify the prediction precision. Four basic chronological steps namely: identification, estimation, diagnostic checking, and forecasting were fitted out in developing the model. Validity of the model was tested using standard graphical explanation of residuals given by Box and Jenkins. As a second step of validation, forecasted values of monthly rainfall were checked using actual data series. After completion of necessary checking and forecast observation, the ARIMA(0, 0, 1) (1,1, 1) 12 was found to be the most effective to predict future precipitation with a 95% confidence interval. It is expected that this long term prediction will help decision makers in efficient scheduling of flood prediction, urban planning, rainwater harvesting and crop management.
机译:在这项研究中,使用Box和Jenkins方法建立了一个季节性ARIMA模型来预测锡尔赫特州的长期降雨。为此,使用了Sylhet站1980年至2010年的降雨数据来建立和检验该模型。该模型使用1980年至2006年的降雨数据开发,而使用2007年至2007年的数据验证预测精度。在开发模型时,装配了四个基本的时间顺序步骤:识别,估计,诊断检查和预测。使用Box和Jenkins给出的残差的标准图形说明测试了模型的有效性。作为验证的第二步,使用实际数据系列检查了每月降雨量的预测值。在完成必要的检查和预报观测之后,发现ARIMA(0,0,1)(1,1,1)12最有效地预测了95%的置信区间内的未来降水。可以预期,这种长期预测将有助于决策者有效地安排洪水预测,城市规划,雨水收集和作物管理。

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