Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm
Author
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-13
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Gold price forecasting has been a hot issue in economics recently.
In this work, wavelet neural network (WNN) combined with a novel artificial bee colony (ABC) algorithm is proposed for this gold price forecasting issue.
In this improved algorithm, the conventional roulette selection strategy is discarded.
Besides, the convergence statuses in a previous cycle of iteration are fully utilized as feedback messages to manipulate the searching intensity in a subsequent cycle.
Experimental results confirm that this new algorithm converges faster than the conventional ABC when tested on some classical benchmark functions and is effective to improve modeling capacity of WNN regarding the gold price forecasting scheme.
American Psychological Association (APA)
Li, Bai. 2014. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-459129
Modern Language Association (MLA)
Li, Bai. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-459129
American Medical Association (AMA)
Li, Bai. Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-459129
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-459129