Prediction of multi-components (chlorine, biomass and substrate concentrations) in water distribution systems using artificial neural network (ANN) models

摘要

Artificial Neural Networks (ANN) models are used to predict residual chlorine, substrate andnbiomass concentrations in a Water Distribution System (WDS). ANN models with differentnarchitectures are developed: a one output ANN model (predicting chlorine, substrate and biomassnindividually), a two output ANN model (predicting chlorine + substrate, chlorine + biomass ornsubstrate + biomass) and a three output ANN model (chlorine + substrate + biomass). This studynis carried out for the Bangalore City and North Marin WDSs. Data for these WDSs is obtainednfrom the multi-component reaction transport model. The models are compared using thencorrelation coefficient (R) and the Mean Absolute Error (MAE). The models developed are able tonpredict, reasonably well, the temporal variations in the chlorine, substrate and biomassnconcentrations. Error analysis is carried out to determine the robustness of the models.