Estimation of water quality index with Neural Network Approaches: a case study

The quality of their water is one of important factors, directly concerned with the health of humans and other living beings. This article describes design and application of feed-forward perceptron neural network model for computing the water quality index (WQI) for Dez reservoir (Iran). two different models were built with ANN, and the statistical performance of the models was determined using statistical parameters such R2 and root mean square error (RMSE). The training RMSE value belonging to the best model was found to be significantly high (RMSE=7.6). The relation between the estimation results of ANN model and the experimental data (R2= 0.97) verifies the model’s success. As a result, ANN proved to be a successful means for WQI estimation using different water quality parameters.

Keywords:

Artificial neural network , Dez Reservoir , water quality.