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Adaptive higher order neural network models and their applications in business

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Xu, S (2009) Adaptive higher order neural network models and their applications in business. In: Artificial Higher Order Neural Networks for Economics and Business. IGI Global, Hershey, New York, pp. 314-329. ISBN 978-159904897-0

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Abstract

Business is a diversified field with general areas of specialisation such as accounting, taxation, stock market, and other financial analysis. Artificial Neural Networks (ANN) have been widely used in applications such as bankruptcy prediction, predicting costs, forecasting revenue, forecasting share prices and exchange rates, processing documents and many more. This chapter introduces an Adaptive Higher Order Neural Network (HONN) model and applies the adaptive model in business applications such as simulating and forecasting share prices. This adaptive HONN model offers significant advantages over traditional Standard ANN models such as much reduced network size, faster training, as well as much improved simulation and forecasting errors, due to their ability to better approximate complex, non-smooth, often discontinuous training data sets. The generalisation ability of this HONN model is explored and discussed.

Item Type: Book Section
Keywords: Higher Order Neural Network, Adaptive Higher Order Neural Network, Adaptive Activation Function, Feedforward Neural Network, Cross Validation, Data Simulation, Financial Forecasting, Financial Prediction.
Publisher: IGI Global
Page Range: pp. 314-329
Additional Information: IGI Global - All Rights Reserved ©2009
Date Deposited: 13 Jan 2009 04:49
Last Modified: 18 Nov 2014 03:54
URI: http://eprints.utas.edu.au/id/eprint/8213
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