In the present paper, different Autoregressive Integrated Moving Average (ARIMA) models were developed to model the carbon dioxide emission by using time series data of f'/> Modeling and Forecasting of Carbon Dioxide Emissions in Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Models
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Modeling and Forecasting of Carbon Dioxide Emissions in Bangladesh Using Autoregressive Integrated Moving Average (ARIMA) Models

机译:孟加拉国二氧化碳排放的建模与预测使用自回归综合移动平均线(Arima)模型

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style="text-align:justify;"> In the present paper, different Autoregressive Integrated Moving Average (ARIMA) models were developed to model the carbon dioxide emission by using time series data of forty-four years from 1972-2015. 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 different ARIMA models, ARIMA (0, 2, 1) is the best fitted model in predicting the emission of carbon dioxide in Bangladesh. Using this best fitted model, the forecasted value of carbon dioxide emission in Bangladesh, for the year 2016, 2017 and 2018 as obtained from ARIMA (0, 2, 1) was obtained as 83.94657 Metric Tons, 89.90464 Metric Tons and 96.28557 Metric Tons respectively.
机译:style =“text-align:证明;”>在本文中,开发了不同的自回归综合移动平均(Arima)模型来通过使用1972 - 2015年的时间序列数据来模拟二十四年的二十四次的二氧化碳排放。在不同的选择测量标准的帮助下评估了这些开发模型的性能,以及这些标准的最小值的模型被认为是最佳预测模型的模型。基于调查结果,已经观察到,出于不同的Arima模型,Arima(0,2,1)是最适合预测孟加拉国二氧化碳排放的最佳拟合模型。使用这一最佳拟合模型,孟加拉国二氧化碳排放量的预测价值,2016年,2016年和2018年从Arima(0,2,1)中获得的83.94657公吨,89.90464公吨和96.28557公吨分别获得。

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