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Application of hybrid GMDH and Least Square Support Vector Machine in energy consumption forecasting

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3 Author(s)
Ahmad Sukri bin Ahmad ; Center of Electrical Energy System, Universiti Teknologi Malaysia (UTM), Johor Darul Ta'zim, Malaysia ; Mohammad Yusri bin Hassan ; Md. Shah bin Majid

Forecasting is a tool to predict the future event with the uncertainty and depending on the historical data. It is important for an upcoming planning event because the forecasting result will deliver the initial view for the future. This paper reviews the Least Square Support Vector Machine (LSSVM) and Group Method of Data Handling (GMDH) used in different application of forecasting. Besides, this paper will highlight the possibility of implementing the hybrid GMDH and LSSVM to achieve better accuracy of building energy consumption forecasting.

Published in:

Power and Energy (PECon), 2012 IEEE International Conference on

Date of Conference:

2-5 Dec. 2012