A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates

Ho Mok Cheong, F 2008, 'A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates', International Journal of Artificial Intelligence and Soft Computing, vol. 1, no. 1, pp. 15-24.


Document type: Journal Article
Collection: Journal Articles

Title A hierarchical fuzzy system with high input dimensions for forecasting foreign exchange rates
Author(s) Ho Mok Cheong, F
Year 2008
Journal name International Journal of Artificial Intelligence and Soft Computing
Volume number 1
Issue number 1
Start page 15
End page 24
Total pages 10
Publisher Inderscience Publishers
Abstract Fuzzy systems suffer from the curse of dimensionality as the number of rules increases exponentially with the number of input dimensions. Although several methods have been proposed for eliminating the combinatorial rule explosion, none of them is fully satisfactory as there are no known fuzzy systems that can handle a large number of inputs so far. In this paper, we describe a method for building fuzzy systems with high input dimensions based on the hierarchical architecture and the MacVicar-Whelan meta-rules. The proposed method is fully automated since a complete fuzzy system is generated from sample input-output data using an Evolutionary Algorithm. We tested the method by building fuzzy systems for two different applications, namely the forecasting of the Mexican and Argentinan pesos exchange rates. In both cases, our approach was successful as both fuzzy systems performed very well.
Subject Conceptual Modelling
Simulation and Modelling
Keyword(s) Argentina
MacVicar-Whelan metarules
Mexico
dimensionality curse
financial engineering
forecasting
fuzzy control
hierarchical fuzzy logic controllers
pesos exchange rates
DOI - identifier 10.1504/IJAISC.2008.021261
ISSN 1755-4950
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 5 times in Scopus Article | Citations
Altmetric details:
Access Statistics: 207 Abstract Views  -  Detailed Statistics
Created: Thu, 16 Dec 2010, 10:48:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us