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Time Series Forecasting of Solid Waste Generation in Arusha City - Tanzania

机译:阿鲁沙市固体废物产生的时间序列预测-坦桑尼亚

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摘要

Statistical time series modeling is widely used in prediction and forecasting studies. This study intends to analyze, compare and select the best time series model for forecasting amount of solid waste generation for the next years in Arusha city - Tanzania among ARMA/ARIMA and Exponential Smoothing models. The past data used are monthly amount of solid waste collected by the city authorities from year 2008 to 2013. The result indicated that ARIMA (1, 1, 1) outperformed other potential models in terms of MAPE, MAD and RMSE measures and hence used to forecast the amount of the solid waste generation for the next years. Keywords: ARIMA models, Exponential Smoothing models, time series, MAPE, MAD, RMSE
机译:统计时间序列建模广​​泛用于预测和预测研究。这项研究旨在分析,比较和选择最佳时间序列模型,以在ARMA / ARIMA和指数平滑模型中预测坦桑尼亚阿鲁沙市未来几年的固体废物产生量。过去使用的数据是城市当局从2008年至2013年每月收集的固体废物量。结果表明,在MAPE,MAD和RMSE措施方面,ARIMA(1、1、1)优于其他潜在模型,因此用于预测未来几年的固体废物产生量。关键字:ARIMA模型,指数平滑模型,时间序列,MAPE,MAD,RMSE

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