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Adaptive higher order neural network models and their applications in business


Xu, S, Adaptive higher order neural network models and their applications in business, Artificial Higher Order Neural Networks for Economics and Business, Information Science Reference, Ming Zhang (ed), Hershey, PA, pp. 314-329. ISBN 978-1-59904-897-0 (2009) [Research Book Chapter]

Copyright Statement

Copyright 2009 IGI Global

DOI: doi:10.4018/978-1-59904-897-0.ch014


Business is a diversified field with general areas of specialisation such as accounting, taxation, stock market, and other financial analysis. Artificial Neural Networks (ANNs) 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 Details

Item Type:Research Book Chapter
Research Division:Information and Computing Sciences
Research Group:Machine learning
Research Field:Neural networks
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Xu, S (Dr Shuxiang Xu)
ID Code:60434
Year Published:2009
Deposited By:Information and Communication Technology
Deposited On:2010-02-05
Last Modified:2015-06-10

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