TIME SERIES PREDICTION USING KNN ALGORITHMS VIA EUCLIDIAN DISTANCE FUNCTION: A CASE OF FOREIGN EXCHANGE RATE PREDICTION
Abstract
International transactions are usually settled in the near future. Exchange rate forecasts are necessary to evaluate the foreign denominated cash flows involved in international transactions. Thus, exchange rate forecasting is very important to evaluate the benefits and risks attached to the international business environment. A forecast represents an expectation about a future value or values of a variable. In this research paper, Researchers use technique known as KNN which belongs to Machine learning subfield of Artificial intelligence. Here researchers develop an experimental setup to predict the value of USD in term of INR for the next day. The MATLAB is used as the developing tool. The interesting results so obtained are presented here.Downloads
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