Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20150
Title: Financial trend forecasting with fuzzy chaotic oscillatory-based neural networks (CONN)
Authors: Kwong, KM
Wong, MHY
Lee, RST
Liu, JNK
Keywords: Financial data processing
Fuzzy set theory
Investment
Neural nets
Issue Date: 2009
Publisher: IEEE
Source: IEEE International Conference on Fuzzy Systems, 2009 : FUZZ-IEEE 2009, 20-24 August 2009, Jeju Island, p. 1947-1952 How to cite?
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.
URI: http://hdl.handle.net/10397/20150
ISBN: 978-1-4244-3596-8
978-1-4244-3597-5 (E-ISBN)
ISSN: 1098-7584
DOI: 10.1109/FUZZY.2009.5277326
Appears in Collections:Conference Paper

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