Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCIS.2010.5518553
Title: Short-term load forecasting using time series analysis: A case study for Singapore
Authors: Deng, J.
Jirutitijaroen, P. 
Keywords: Short-term load forecasting
Singapore data
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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