Designing Perceptron Three-layered Neural Network for Predicting Dollar- Franc Currency Pair in International Exchange Market


Authors

Danial Khoonmirzaie - Faculty of Engineeing, Payame Nur University of Tehran. Somaye Rasouli - Faculty of Engineeing, shomal University, Amol, Iran. Ensiye Farrokhi - Faculty of Engineeing, Payame Nur University of Tehran.


Abstract

International financial markets like exchange market are among the most dynamic markets in the capital markets available in which investing needs enough knowledge and experience. So we decided to invent a system so that it can forecast trend created in exchange market. There are a lot of wide transactional strategies for buy and selling of exchange symbols which here we used science of artificial neural network in this article. Final results of the predictions and percent of Mean square error of the network is calculated after defining neural network and training by Matlab software. Training of desired neural network is achieved by 2010 price data in order to mean square error decrease to 2.15e-6 and at comparison against newest of research show proper improvement.


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ISRP Style

Danial Khoonmirzaie, Somaye Rasouli, Ensiye Farrokhi, Designing Perceptron Three-layered Neural Network for Predicting Dollar- Franc Currency Pair in International Exchange Market, Journal of Mathematics and Computer Science, 8 (2014), no. 2, 98 - 104

AMA Style

Khoonmirzaie Danial, Rasouli Somaye, Farrokhi Ensiye, Designing Perceptron Three-layered Neural Network for Predicting Dollar- Franc Currency Pair in International Exchange Market. J Math Comput SCI-JM. (2014); 8(2):98 - 104

Chicago/Turabian Style

Khoonmirzaie, Danial, Rasouli, Somaye, Farrokhi, Ensiye. "Designing Perceptron Three-layered Neural Network for Predicting Dollar- Franc Currency Pair in International Exchange Market." Journal of Mathematics and Computer Science, 8, no. 2 (2014): 98 - 104


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