Accurate Forecasting Prediction of Foreign Exchange Rate Using Neural Network Algorithms: A STUDY?

Data mining is a form of knowledge discovery essential for solving problems in a specific domain. Classification is a technique used for discovering classes of unknown data. Several major kinds of classification method including decision tree induction, Bayesian networks, k-nearest neighbour classifier, case-based reasoning, genetic algorithm, fuzzy logic techniques and neural networks etc. A neural network is a massively parallel distributed processor that has a natural propensity for storing experimental knowledge and making it available for use. Artificial Neural Networks [ANN] are nonlinear information processing devices which are built from interconnected elementary processing devices called neurons. The goal of this study is to find the efficiency of the existing artificial neural network algorithm on forecasting foreign exchange rate. Back propagation Algorithm, Hidden Markov Model, recurrent neural networks are the algorithms selected for the study. The back propagation algorithm gives finite accuracy in foreign exchange rate.