Genetic algorithm for neural networks optimization

Bina R. Setyawati; Robert C. Creese; Sidharta Sahirman

doi:10.1117/12.578064

11 November 2004 Genetic algorithm for neural networks optimization

Bina R. Setyawati, Robert C. Creese, Sidharta Sahirman

Proceedings Volume 5605, Intelligent Systems in Design and Manufacturing V; (2004) https://doi.org/10.1117/12.578064
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States

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®.

Citation Download Citation

Bina R. Setyawati, Robert C. Creese, and Sidharta Sahirman "Genetic algorithm for neural networks optimization", Proc. SPIE 5605, Intelligent Systems in Design and Manufacturing V, (11 November 2004); https://doi.org/10.1117/12.578064

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