MATHEMATICAL MODEL FOR DISSOLVED OXYGEN PREDICTION IN CIRATA RESERVOIR, WEST JAVA BY USING ARTIFICIAL NEURAL NETWORK

Abstract

Cirata reservoir is one of the reservoirs which suffer eutrophication with an indication of rapid growth of water hyacinth and mass fish deaths as a result of lack of oxygen. This paper presents the implementation and performance of mathematical model to predict the concentration of dissolved oxygen in Cirata Reservoir, West Java by using Artificial Neural Network (ANN). The simulation program was created using Visual Studio 2012 C# software with ANN model implemented in it. Prediction process was carried out by training process followed by a testing process using weights that have been obtained from training process. ANN model for predicting dissolved oxygen in Cirata reservoir shows the best performance with correlation coefficient value of 77.44%, Root Mean Square Error (RMSE) = 0.12 and Willmott’s Index of Agreement (WIA) = 0.72.