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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/3948

Title: An Adaptive BP Learning Algorithm for Stock Market Prediction
Authors: Kin, Keung Lai
Lean, Yu
Shouyang, Wang
Keywords: Adaptive learning
optimal learning rate
stock market prediction
Issue Date: Nov-2005
Publisher: JAIST Press
Abstract: In this study, a novel adaptive learning algorithm for back-propagation neural network (BPNN) based on optimized instantaneous learning rates is proposed. In this new algorithm, the optimized adaptive learning rates are used to adjust the weight changes dynamically. For illustration and testing purposes the proposed algorithm is applied to stock market prediction.
Description: The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2158, Kobe, Japan
Symposium 3, Session 7 : Intelligent Information Technology and Applications Computational Intelligence (1)
Language: ENG
URI: http://hdl.handle.net/10119/3948
ISBN: 4-903092-02-X
Appears in Collections:IFSR 2005

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