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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| 主要な著者: | , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Research India Publications
2016
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| 主題: | |
| オンライン･アクセス: | 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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| 要約: | 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. |
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