Foreign Exchange Price Prediction Using Artificial Neural Network Optimized by Salp Swarm Algorithm

This work is focused to design a network in terms of predicting the exchange price of Foreign Rupees in accordance to other currencies through a proper analysis of various past datasets. The prediction of the exchange rate has been done between world’s traded currencies such as USD versus INR. The algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA) has been applied to optimize the Artificial Neural Network (ANN) for the foreign exchange prediction. Two performance metrics has been considered for tabulating and comparing the models are: Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The predicted outcome gives the efficiency of the model over various popular models.