DocumentCode :
1629195
Title :
Financial trend forecasting with fuzzy chaotic oscillatory-based neural networks (CONN)
Author :
Kwong, K.M. ; Wong, Max H Y ; Lee, Raymond S T ; Liu, James N K
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2009
Firstpage :
1947
Lastpage :
1952
Abstract :
This paper describes a methodology for financial prediction by using an advanced paradigm from computational intelligence - Chaotic Oscillatory-based Neural Networks (CONN) and aid with fuzzy membership function. The method uses financial market data to predict market trends over a certain period of time. This approach may have a wide variety of applications but from financial forecasting perspective, it can be used to identify and forecast market patterns for providing valuable and useful advices to investors for making investment decisions.
Keywords :
financial data processing; fuzzy set theory; investment; neural nets; computational intelligence; financial market data; financial trend forecasting; fuzzy chaotic oscillatory-based neural networks; fuzzy membership function; investment decisions; Biological neural networks; Chaos; Cotton; Economic forecasting; Fuzzy neural networks; Neural networks; Neurons; Oscillators; Predictive models; Wind forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
ISSN :
1098-7584
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2009.5277326
Filename :
5277326
Link To Document :
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