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Proceedings Paper

Genetic algorithm for neural networks optimization
Author(s): Bina R. Setyawati; Robert C. Creese; Sidharta Sahirman
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Paper Abstract

This paper examines the forecasting performance of multi-layer feed forward neural networks in modeling a particular foreign exchange rates, i.e. Japanese Yen/US Dollar. The effects of two learning methods, Back Propagation and Genetic Algorithm, in which the neural network topology and other parameters fixed, were investigated. The early results indicate that the application of this hybrid system seems to be well suited for the forecasting of foreign exchange rates. The Neural Networks and Genetic Algorithm were programmed using MATLAB®.

Paper Details

Date Published: 11 November 2004
PDF: 8 pages
Proc. SPIE 5605, Intelligent Systems in Design and Manufacturing V, (11 November 2004); doi: 10.1117/12.578064
Show Author Affiliations
Bina R. Setyawati, West Virginia Univ. (United States)
Robert C. Creese, West Virginia Univ. (United States)
Sidharta Sahirman, West Virginia Univ. (United States)

Published in SPIE Proceedings Vol. 5605:
Intelligent Systems in Design and Manufacturing V
Bhaskaran Gopalakrishnan, Editor(s)

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