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

Idorenyin Markson; Mfonobong Charles Uko; Aneke Chikezie

doi:doi:10.11648/j.ajsea.20170603.12

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

Idorenyin Markson, Mfonobong Charles Uko, Aneke Chikezie

Published in American Journal of Software Engineering and Applications (Volume 6, Issue 3)

Received: 29 January 2017 Accepted: 30 March 2017 Published: 12 June 2017

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Abstract

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 r2 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.

Published in	American Journal of Software Engineering and Applications (Volume 6, Issue 3)
DOI	10.11648/j.ajsea.20170603.12
Page(s)	67-73
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Moving Average Model, Autoregressive Moving Average Model, Industrial Electricity Consumption, Prediction Accuracy, Time Series Models

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APA Style

Idorenyin Markson, Mfonobong Charles Uko, Aneke Chikezie. (2017). Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. American Journal of Software Engineering and Applications, 6(3), 67-73. https://doi.org/10.11648/j.ajsea.20170603.12

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ACS Style

Idorenyin Markson; Mfonobong Charles Uko; Aneke Chikezie. Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. Am. J. Softw. Eng. Appl. 2017, 6(3), 67-73. doi: 10.11648/j.ajsea.20170603.12

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AMA Style

Idorenyin Markson, Mfonobong Charles Uko, Aneke Chikezie. Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. Am J Softw Eng Appl. 2017;6(3):67-73. doi: 10.11648/j.ajsea.20170603.12

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@article{10.11648/j.ajsea.20170603.12,
  author = {Idorenyin Markson and Mfonobong Charles Uko and Aneke Chikezie},
  title = {Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria},
  journal = {American Journal of Software Engineering and Applications},
  volume = {6},
  number = {3},
  pages = {67-73},
  doi = {10.11648/j.ajsea.20170603.12},
  url = {https://doi.org/10.11648/j.ajsea.20170603.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20170603.12},
  abstract = {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 r2 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.},
 year = {2017}
}

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TY  - JOUR
T1  - Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria
AU  - Idorenyin Markson
AU  - Mfonobong Charles Uko
AU  - Aneke Chikezie
Y1  - 2017/06/12
PY  - 2017
N1  - https://doi.org/10.11648/j.ajsea.20170603.12
DO  - 10.11648/j.ajsea.20170603.12
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 67
EP  - 73
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20170603.12
AB  - 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 r2 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.
VL  - 6
IS  - 3
ER  -

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Author Information

Idorenyin Markson

Department of Mechanical Engineering, University of Uyo, Uyo, Nigeria
Mfonobong Charles Uko

Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo, Nigeria
Aneke Chikezie

Department of Electrical/Electronic and Computer Engineering, University of Uyo, Uyo, Nigeria

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APA Style

Idorenyin Markson, Mfonobong Charles Uko, Aneke Chikezie. (2017). Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. American Journal of Software Engineering and Applications, 6(3), 67-73. https://doi.org/10.11648/j.ajsea.20170603.12

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ACS Style

Idorenyin Markson; Mfonobong Charles Uko; Aneke Chikezie. Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. Am. J. Softw. Eng. Appl. 2017, 6(3), 67-73. doi: 10.11648/j.ajsea.20170603.12

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AMA Style

Idorenyin Markson, Mfonobong Charles Uko, Aneke Chikezie. Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria. Am J Softw Eng Appl. 2017;6(3):67-73. doi: 10.11648/j.ajsea.20170603.12

Copy | Download

@article{10.11648/j.ajsea.20170603.12,
  author = {Idorenyin Markson and Mfonobong Charles Uko and Aneke Chikezie},
  title = {Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria},
  journal = {American Journal of Software Engineering and Applications},
  volume = {6},
  number = {3},
  pages = {67-73},
  doi = {10.11648/j.ajsea.20170603.12},
  url = {https://doi.org/10.11648/j.ajsea.20170603.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20170603.12},
  abstract = {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 r2 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.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Evaluation of Moving Average Model and Autoregressive Moving Average Model (ARMA) for Prediction of Industrial Electricity Consumption in Nigeria
AU  - Idorenyin Markson
AU  - Mfonobong Charles Uko
AU  - Aneke Chikezie
Y1  - 2017/06/12
PY  - 2017
N1  - https://doi.org/10.11648/j.ajsea.20170603.12
DO  - 10.11648/j.ajsea.20170603.12
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 67
EP  - 73
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20170603.12
AB  - 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 r2 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.
VL  - 6
IS  - 3
ER  -

Copy | Download