利用自回归综合移动平均(ARIMA)模型对孟加拉国茶叶生产进行建模

Abdur Rahman
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引用次数: 2

摘要

本文利用1990-2013年24年的时间序列数据,建立了不同的自回归综合移动平均(ARIMA)模型对茶叶产量进行预测。利用不同的选择度量标准对这些模型的性能进行评价,并将这些标准值最小的模型视为最佳预测模型。根据研究结果,可以观察到,在11个ARIMA模型中,ARIMA(1,1,2)是预测孟加拉国茶叶产量的最佳拟合模型,从ARIMA(1,1,2)中获得的2014年,2015年和2016年孟加拉国茶叶产量的预测值分别为6556.8万公斤,6786.7万公斤和6099.7万公斤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of Tea Production in Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Model
In the present paper, different Autoregressive Integrated Moving Average (ARIMA) models were developed to forecast the tea production by using time series data of twenty-four years from 1990-2013. The performance of these developed models was assessed with the help of different selection measure criteria and the model having minimum value of these criteria considered as the best forecasting model. Based on findings, it has been observed that out of eleven ARIMA models, ARIMA (1,1,2) is the best fitted model in predicting the production of tea in Bangladesh and the forecasted value of tea production in Bangladesh, for the year 2014, 2015 and 2016 as obtained from ARIMA (1,1,2) was obtained as 65.568 Million Kilogram, 67.867 Million Kilogram and 60.997 Million Kilogram.
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