The aim of this study is to examine the accuracy of two different artificial neural network (ANN) techniques, the multilayer perceptron (MLP) and radial basis neural network (RBNN), to estimate dissolved oxygen (DO) concentration. The ANN results are compared with multilinear regression (MLR) model. The neural network model is developed using experimental data collected from the upstream (USGS Station No: 07105530) and downstream (USGS Station No: 07106000) stations on Foundation Creek, CO. The input variables used for the ANN models are water pH, temperature, electrical conductivity, and discharge. The determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) statistics are used for the evaluation of the applied models. The MLP and RBNN models are also compared with MLR model in estimating the DO of the downstream station by using the input parameters of the upstream station. Comparison results indicate that the RBNN model performs better than the MLP and MLR mo...

Dissolved oxygen, one of the most important water quality parameters, is a crucial parameter for the aquatic ecosystems. In this study, some advanced chemometric techniques included in a multi-layer perceptron, radial basis neural network, and two different adaptive neuro-fuzzy inference system methods are developed to model dissolved oxygen concentration. Moreover the estimations of these models are compared with the multiple linear regression. In this context, monthly mean quantities of the temperature, pH, electrical conductivity, discharge and dissolved oxygen data recorded at Broad River near Carlisle, SC in USA are used. The accuracy of the models is compared with one other by using determination coefficient, mean absolute error, root mean square error and mean absolute relative error statistics. Results indicate that radial basis neural network method performs better than the other methods in modelling monthly mean dissolved oxygen concentration. The temperature, pH, electrical conductivity, and discharge are found to be effective on dissolved oxygen concentration.