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Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria

机译:预测尼日利亚工业用电量的移动平均模型和自回归移动平均模型(ARMA)的评估

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In this paper, evaluation of moving average model and autoregressive moving average model (ARMA) for prediction of industrial electricity consumption in Nigeria is presented. Industrial electricity consumption data obtained from Central Bank of Nigeria (CBN) Statistical Bulletin for the year 1979-2014 is used to determine the model parameters and prediction performance in terms of Root Mean Square Error (RMSE) and Coefficient of determination r~2 values. The results show that the Autoregressive Moving Average (ARMA) model with coefficient of determination value of 66.0% and RMSE value of 68.628 gives better prediction performance than the Moving Average with coefficient of determination value of 42.6% and value of 84.749. However, coefficient of determination value of 66% is not particularly adequate for acceptable prediction accuracy. In that case, for better prediction accuracy for the industrial electricity consumption in Nigeria, other models may need to be examined apart from the two models considered in this paper.
机译:本文介绍了移动平均模型和自回归移动平均模型(ARMA)在尼日利亚工业用电量预测中的评估。从尼日利亚中央银行(CBN)统计公报获得的1979-2014年的工业用电量数据用于确定模型参数和预测性能(均方根误差(RMSE)和确定系数r〜2值)。结果表明,确定系数为66.0%,RMSE值为68.628的自回归移动平均值(ARMA)模型比确定系数为42.6%和84.749的移动平均值具有更好的预测性能。但是,对于可接受的预测精度而言,确定系数值的66%并不是特别合适。在这种情况下,为了更好地预测尼日利亚的工业用电量,除了本文考虑的两个模型外,可能还需要检查其他模型。

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