Exploring the use of Water Cycle Optimization Algorithm for Foreign Exchange Prediction | Zendy

Arup Kumar Mohanty | Zendy; Debahuti Mishra | Zendy

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Exploring the use of Water Cycle Optimization Algorithm for Foreign Exchange Prediction

Author(s) -

Arup Kumar Mohanty,

Debahuti Mishra

Publication year - 2019

Publication title -

international journal of innovative technology and exploring engineering

Language(s) - English

Resource type - Journals

ISSN - 2278-3075

DOI - 10.35940/ijitee.j8793.0881019

Subject(s) - mean squared error , mean absolute error , artificial neural network , foreign exchange , mean squared prediction error , liberian dollar , computer science , us dollar , optimization algorithm , approximation error , econometrics , exchange rate , algorithm , machine learning , mathematics , statistics , mathematical optimization , economics , finance , monetary economics , macroeconomics

The aim of this paper is to model a network and predict the exchange price of United States Dollar to Indian Rupees using daily exchange rates from Dec 18, 1991-Jul 19, 2007. In this paper, Water Cycle Optimization (WCA) technique has been used to optimize the Artificial Neural Network (ANN) for Foreign Exchange prediction on the basis of their predictive performance. The performance metrics considered for the evaluation of the models are root mean square error (RMSE) and mean absolute error (MAE). The tabulated outcome shows the efficiency of the model over other popular models

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