Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2142
Title: Development and performance evaluation of a novel knowledge guided artificial neural network (KGANN) model for exchange rate prediction
Authors: Jena, Pradyot Ranjan
Majhi, Ritanjali
Majhi, Babita
Keywords: Artificial neural network
Neural network(FLANN);
Issue Date: 2015
Publisher: Journal of King Saud University - Computer and Information Sciences
Citation: 10.1016/j.jksuci.2015.01.002
Abstract: Thispaperpresentsanewadaptiveforecastingmodelusingaknowledgeguidedartificial neuralnetwork(KGANN)structureforefficientpredictionofexchangerate.Thenewstructurehas twoparallel systems.Thefirst systemisaleastmeansquare(LMS) trainedadaptive linearcombiner,whereas thesecondsystememploysanadaptiveFLANNmodel tosupplement theknowledgebasewithanobjective to improve its performance value. Theoutput of a trainedLMS model isaddedtoanadaptiveFLANNmodeltoprovideamoreaccurateexchangeratecompared tothatpredictedbyeitherasimpleLMSoraFLANNmodel.Thisfindinghasbeendemonstrated throughanexhaustingcomputer simulationstudyandusing real lifedata.Thus theproposed KGANNisanefficient forecastingmodel forexchangerateprediction.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/2142
Appears in Collections:School of Management

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