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|Title:||Short-term load forecasting using time series analysis: A case study for Singapore||Authors:||Deng, J.
|Keywords:||Short-term load forecasting
Time series analysis
|Issue Date:||2010||Citation:||Deng, J.,Jirutitijaroen, P. (2010). Short-term load forecasting using time series analysis: A case study for Singapore. 2010 IEEE Conference on Cybernetics and Intelligent Systems, CIS 2010 : 231-236. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCIS.2010.5518553||Abstract:||This paper presents time series analysis for short-term Singapore electricity demand forecasting. Two time series models are proposed, namely, the multiplicative decomposition model and the seasonal ARIMA Model. Forecasting errors of both models are computed and compared. Results show that both time series models can accurately predict the short-term Singapore demand and that the Multiplicative decomposition model slightly outperforms the seasonal ARIMA model. © 2010 IEEE.||Source Title:||2010 IEEE Conference on Cybernetics and Intelligent Systems, CIS 2010||URI:||http://scholarbank.nus.edu.sg/handle/10635/71761||ISBN:||9781424464999||DOI:||10.1109/ICCIS.2010.5518553|
|Appears in Collections:||Staff Publications|
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