Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models

机译：美国主要能源消费数据预测：阿玛哈和冬温模型的比较

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This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2).

机译：该研究有目的是基于MAE，RS，MSE和RMS标准比较Arima Model和Holt-Winters模型，以预测美国的主要能量消耗总数据。这项研究的数据从1973年1月到2016年1月到2016年12月。使用R软件将处理此数据。基于已经完成的数据分析结果，发现Holt-Winters添加类型（MSE：258350.1）的模型是预测美国的主要能耗总数据中最合适的模型。与Holt-Winters乘法型（MSE：262260,4）和Arima季节模型相比，该模型更适合（MSE：723502,2）。

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《Electronic and Green Materials International Conference》|2017年|various paging|共7页
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A. Rahman; A. S. Ahmar;
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中图分类计量学;
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Forecasting of primary energy consumption data in the United States: A comparison between ARIMA and Holter-Winters models

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