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Application of hybrid GMDH and least square support vector machine in energy consumption forecasting

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)...

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Main Authors: Ahmad, Ahmad Sukri, Hassan, Mohammad Yusri, Majid, Md. Shah
Format: Conference or Workshop Item
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/34002/
http://ieeexplore.ieee.org/document/6450193/
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id my.utm.34002
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spelling my.utm.340022017-09-26T06:43:45Z http://eprints.utm.my/id/eprint/34002/ Application of hybrid GMDH and least square support vector machine in energy consumption forecasting Ahmad, Ahmad Sukri Hassan, Mohammad Yusri Majid, Md. Shah TK Electrical engineering. Electronics Nuclear engineering 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. 2012 Conference or Workshop Item PeerReviewed 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. http://ieeexplore.ieee.org/document/6450193/
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ahmad, Ahmad Sukri
Hassan, Mohammad Yusri
Majid, Md. Shah
Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
description 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.
format Conference or Workshop Item
author Ahmad, Ahmad Sukri
Hassan, Mohammad Yusri
Majid, Md. Shah
author_facet Ahmad, Ahmad Sukri
Hassan, Mohammad Yusri
Majid, Md. Shah
author_sort Ahmad, Ahmad Sukri
title Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
title_short Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
title_full Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
title_fullStr Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
title_full_unstemmed Application of hybrid GMDH and least square support vector machine in energy consumption forecasting
title_sort application of hybrid gmdh and least square support vector machine in energy consumption forecasting
publishDate 2012
url http://eprints.utm.my/id/eprint/34002/
http://ieeexplore.ieee.org/document/6450193/
_version_ 1643649490132926464
score 13.214268

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