Makaleyi göster

In this study, three single Artificial Intelligence (AI) based models i.e., Back Propagation Neural Network (BPNN), Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and a linear Auto Regressive Integrated Moving Average (ARIMA) model as well as three different ensemble techniques i.e., Simple average ensemble (SAE), weighted average ensemble (WAE) and neural network ensemble (NNE) are applied for single and multi-step ahead modeling of dissolve oxygen (DO) in the Yamuna River, India. In this context, DO, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Discharge (Q), pH, Ammonia (NH3), Water Temperature (WT) data for three different stations i.e., Hathnikund (SL1), Nizamuddin (SL2) and Udi (SL3) recorded by central pollution control board were used. The performance accuracy of the models was determined using Determination Coefficient (DC …