2026-09-21T17:16:26Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/3266 2021-12-13T00:42:30Z 1582963302567:1597824273898 user-ucsy

Forecasting for Myanmar Currency Exchange Rates By using Back Propagation Neural Network Myint, Aye Nandar Khine, May Aye Khaing, Myo Kay Nowadays, forecasting of exchange ratesplays an important role in internationaleconomics. Additional to basic economic andfinancial news, investors and traders employ intheir decision process technical tools to analyzethe transaction data.In this paper, the system based on neuralnetworks implemented for forecasting MyanmarCurrency exchange ratesusing artificial neuralnetwork. The system uses back-propagationalgorithm to train the exchange rates. Feedforward neural network is used to improve theefficiency of the back-propagation. MultilayerPerceptron (MLP) network is the mainarchitecture. Network architecture parametersespecially number of input and number of hiddenlayers are analyzed.System performance isevaluated in terms of Mean Absolute Error(MAE). Daily historical price data for currencypairs for the last three years are inputted to thesystem. The system is implemented usingprogramming language C#. 2017-12-27 http://hdl.handle.net/20.500.12678/0000003266 https://meral.edu.mm/records/3266