Forecasting foreign exchange rates using CRO based different variants of FLANN and performance analysis
by Kishore Kumar Sahu; Soumya Ranjan Sahu; Sarat Chandra Nayak; Himansu Sekhar Behera
International Journal of Computational Systems Engineering (IJCSYSE), Vol. 2, No. 4, 2016

Abstract: Globalisation has been the most influential shift of human civilisation since its inception. Foreign exchange (FOREX) market rates played a pivotal role in this extravagant change. FOREX rates have been a vital factor while deciding any international deals among the countries. Though FOREX exhibits a nonlinear trend, evolutionary techniques like artificial neural networks (ANNs) make it possible to predict. This paper deliberates the prediction using different variants of FLANN, i.e., CFLANN, LFLANN, PFLANN and TFLANN with chemical reaction optimisation (CRO) technique by using the real-time series of rupees, euro, yen and pound. Experimental analysis indicates that PFLANN and LFLANN perform better in most of the cases.

Online publication date: Fri, 06-Jan-2017

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