Information systems based on neural network and wavelet methods with application to decision making, modeling and prediction tasks

D.A. Karras (University of Ioannina, Department of Informatics, Ioannina, Greece)
S.A. Karkanis (NCSR “Demokritos”, Institute of Nuclear Technology, Ag. Paraskevi, Greece)
B.G. Mertzios (Democritus University of Thrace, Department of Electrical and Computer Engineering, Xanthi, Greece)

Kybernetes

ISSN: 0368-492X

Publication date: 1 April 1998

Abstract

This paper suggests a novel methodology for building robust information processing systems based on wavelets and artificial neural networks (ANN) to be applied either in decision‐making tasks based on image information or in signal prediction and modeling tasks. The efficiency of such systems is increased when they simultaneously use input information in its original and wavelet transformed form, invoking ANN technology to fuse the two different types of input. A quality control decision‐making system as well as a signal prediction system have been developed to illustrate the validity of our approach. The first one offers a solution to the problem of defect recognition for quality control systems. The second application improves the quality of time series prediction and signal modeling in the domain of NMR. The accuracy obtained shows that the proposed methodology deserves the attention of designers of effective information processing systems.

Keywords

Citation

Karras, D., Karkanis, S. and Mertzios, B. (1998), "Information systems based on neural network and wavelet methods with application to decision making, modeling and prediction tasks", Kybernetes, Vol. 27 No. 3, pp. 224-236. https://doi.org/10.1108/03684929810209405

Download as .RIS

Publisher

:

MCB UP Ltd

Copyright © 1998, MCB UP Limited

Please note you might not have access to this content

You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
If you would like to contact us about accessing this content, click the button and fill out the form.
To rent this content from Deepdyve, please click the button.