River water modelling prediction using multi-linear regression, artificial neural network, and adaptive neuro-fuzzy inference system techniques

Abstract In this study, multi linear regression ( MLR), artificial neural network (ANN) and adaptive neuro fuzzy inference system(ANFIS) techniques were developed to predict the Dissolve oxygen concentration at down stream of Agra city, using monthly input data which are dissolve oxygen(DO), pH, biological oxygen demand(BOD) and water temperature (WT) at three different places viz, Agra upstream, middle stream and downstream. Initially, 11 input parameters for all the three locations were used except DO at the downstream, then, 7 input for middle and downstream except DO at the target location and finally the downstream location was considered in the analysis. The performance was evaluated using determination coefficient (DC) and root mean square error (RMSE), the result of DO showed that both the ANN and ANFIS can be applied in modelling DO concentration in Agra city, and also indicate that, ANN model is slightly better than ANFIS and also indicates a considerable superiority to MLR.

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