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ARAR algorithm in forecasting electricity load demand in Malaysia

Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchm...

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Main Authors: Miswan, Nor Hamizah, Hussin, Nor Hafizah, Mohd Said, Rahaini, Hamzah, Khairum, Ahmad, Emy Zairah
Format: Article
Language:English
Published: Research India Publications 2016
Subjects:
T Technology (General)
Online Access:http://eprints.utem.edu.my/id/eprint/16996/2/19_43000-%20GJPAM%2097%20ok%20361-367%20author%20self1.pdf
http://eprints.utem.edu.my/id/eprint/16996/
http://www.ripublication.com/gjpam16/gjpamv12n1_32.pdf
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spelling my.utem.eprints.169962023-07-18T12:08:13Z http://eprints.utem.edu.my/id/eprint/16996/ ARAR algorithm in forecasting electricity load demand in Malaysia Miswan, Nor Hamizah Hussin, Nor Hafizah Mohd Said, Rahaini Hamzah, Khairum Ahmad, Emy Zairah T Technology (General) Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model. Research India Publications 2016 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/16996/2/19_43000-%20GJPAM%2097%20ok%20361-367%20author%20self1.pdf Miswan, Nor Hamizah and Hussin, Nor Hafizah and Mohd Said, Rahaini and Hamzah, Khairum and Ahmad, Emy Zairah (2016) ARAR algorithm in forecasting electricity load demand in Malaysia. Global Journal Of Pure And Applied Mathematics, 12 (1). pp. 361-367. ISSN 0973-1768 http://www.ripublication.com/gjpam16/gjpamv12n1_32.pdf
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Miswan, Nor Hamizah
Hussin, Nor Hafizah
Mohd Said, Rahaini
Hamzah, Khairum
Ahmad, Emy Zairah
ARAR algorithm in forecasting electricity load demand in Malaysia
description Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model.
format Article
author Miswan, Nor Hamizah
Hussin, Nor Hafizah
Mohd Said, Rahaini
Hamzah, Khairum
Ahmad, Emy Zairah
author_facet Miswan, Nor Hamizah
Hussin, Nor Hafizah
Mohd Said, Rahaini
Hamzah, Khairum
Ahmad, Emy Zairah
author_sort Miswan, Nor Hamizah
title ARAR algorithm in forecasting electricity load demand in Malaysia
title_short ARAR algorithm in forecasting electricity load demand in Malaysia
title_full ARAR algorithm in forecasting electricity load demand in Malaysia
title_fullStr ARAR algorithm in forecasting electricity load demand in Malaysia
title_full_unstemmed ARAR algorithm in forecasting electricity load demand in Malaysia
title_sort arar algorithm in forecasting electricity load demand in malaysia
publisher Research India Publications
publishDate 2016
url http://eprints.utem.edu.my/id/eprint/16996/2/19_43000-%20GJPAM%2097%20ok%20361-367%20author%20self1.pdf
http://eprints.utem.edu.my/id/eprint/16996/
http://www.ripublication.com/gjpam16/gjpamv12n1_32.pdf
_version_ 1772816001699676160
score 13.211869

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