Yusof, Yuhanis and Kamaruddin, Siti Sakira and Husni, Husniza and Ku-Mahamud, Ku Ruhana and Mustaffa, Zuriani (2013) Forecasting model based on LSSVM and ABC for natural resource commodity. International Journal of Computer Theory and Engineering, 5 (6). pp. 906-909. ISSN 1793-8201

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Abstract

Reliable forecast of the price of natural resource commodity is of interest for a wide range of applications.This includes generating macroeconomic projections and in assessing macroeconomic risks.Various approaches have been introduced in developing the required forecasting models.In this paper, a forecasting model based on an optimized Least Squares Support Vector Machine is proposed.The determination of hyper-parameters is performed using a nature inspired algorithm, Artificial Bee Colony.The proposed forecasting model is realized is gold price forecasting.The undertaken experiments showed that the prediction accuracy and Mean Absolute Percentage Error produced by the proposed model is better compared on the one produced using Least Squares Support Vector Machine as an individual.

Item Type:	Article
Uncontrolled Keywords:	Artificial bee colony, least squares support vector machine, swarm computing, forecasting, optimization.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	College of Arts and Sciences
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	24 Dec 2013 02:27
Last Modified:	24 Dec 2013 02:27
URI:	https://repo.uum.edu.my/id/eprint/9841

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