DocumentCode
477685
Title
Enhancing the Performance of the Fuzzy System Approach to Prediction
Author
Nguyen, Thi Thanh ; Peterson, Jim
Author_Institution
Sch. of Geogr. & Environ. Sci., Monash Univ., Clayton, VIC
Volume
1
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
259
Lastpage
265
Abstract
Using time-series data, and testing the value of incorporating genetic algorithm, momentum technique, event-knowledge, selective presentation learning (under the SEL algorithm) and new training criteria (for financial time series), it is demonstrated that significant improvement in predictability accrues in deployment of the Standard Additive Model (SAM) during application of the fuzzy set approach to forecasting.
Keywords
forecasting theory; fuzzy set theory; genetic algorithms; time series; event-knowledge; financial time series; fuzzy set approach; fuzzy system; genetic algorithm; momentum technique; selective presentation learning; standard additive model; time-series data; Algorithm design and analysis; Explosions; Function approximation; Fuzzy sets; Fuzzy systems; Genetic algorithms; Geography; Measurement standards; Predictive models; System testing; Standard Additive Model; function approximation; fuzzy system; time-series prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location
Shandong
Print_ISBN
978-0-7695-3305-6
Type
conf
DOI
10.1109/FSKD.2008.198
Filename
4665980
Link To Document