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GA-SVM Based Framework for Time Series Forecasting | IEEE Conference Publication | IEEE Xplore

GA-SVM Based Framework for Time Series Forecasting


Abstract:

A framework (hereby named GA-SVM) for time series forecasting was formed by integration of the particular power of Genetic Algorithms (GAs) with the modeling power of the...Show More

Abstract:

A framework (hereby named GA-SVM) for time series forecasting was formed by integration of the particular power of Genetic Algorithms (GAs) with the modeling power of the Support Vector Machine (SVM). The proposed system has potential to capture the benefits of both fascinating fields into a single framework. GAs offer high capability in choosing inputs that are relevant and necessary in predicting dependent variables. With these selected inputs, SVM becomes more accurate in modeling the estimation problems. Experiments demonstrated that the integrated GA-SVM approach is superior compared to conventional SVM applications.
Date of Conference: 14-16 August 2009
Date Added to IEEE Xplore: 28 December 2009
Print ISBN:978-0-7695-3736-8

ISSN Information:

Conference Location: Tianjian, China

References

References is not available for this document.