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Training LSSVM with GWO for Price Forecasting

Zuriani, Mustaffa and M. H., Sulaiman and M. N. M., Kahar (2015) Training LSSVM with GWO for Price Forecasting. In: 4th International Conference on Informatics, Electronics and Vision (ICIEV2015), 15-18 Jun 2015 , Fukuoka, Japan. pp. 1-6..

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Abstract

This paper presents a hybrid forecasting model namely Grey Wolf Optimizer-Least Squares Support Vector Machines (GWO-LSSVM). In this study, a great deal of attention was paid in determining LSSVM’s hyper parameters. For that matter, the GWO is utilized an optimization tool for optimizing the said hyper parameters. Realized in gold price forecasting, the feasibility of GWO-LSSVM is measured based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Percentage Error (RMSPE). Upon completing the simulation tasks, the comparison against two hybrid methods suggested that the GWO-LSSVM capable to produce lower forecasting error as compared to the identified forecasting techniques.

Item Type: Conference or Workshop Item (Speech)
Additional Information: ISBN: 978-1-4673-6901-5
Uncontrolled Keywords: Grey Wolf Optimizer, Least Squares Support Vector Machiens, Time series forecasting
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 04 Dec 2015 02:45
Last Modified: 26 Feb 2018 08:03
URI: http://umpir.ump.edu.my/id/eprint/10907
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