Ahmad, Ahmad Sukri and Hassan, Mohammad Yusri and Majid, Md. Shah (2012) Application of hybrid GMDH and least square support vector machine in energy consumption forecasting. In: 2012 IEEE International Conference on Power & Energy (PECON 2012), 2-5 Dec 2012, Kota Kinabalu, Malaysia.
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Official URL: http://ieeexplore.ieee.org/document/6450193/
Abstract
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Forecasting, support vector machines, buildings |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Electrical Engineering |
| ID Code: | 34002 |
| Deposited By: | Liza Porijo |
| Deposited On: | 22 Aug 2017 00:52 |
| Last Modified: | 26 Sep 2017 06:43 |
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