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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Research India Publications
2016
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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 |
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| topic |
T Technology (General) |
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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 |
13.251813 |