Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

Modeling and optimization of activated sludge bulking for a real wastewater treatment plant using hybrid artificial neural networks-genetic algorithm approach

“…A large spread value results in a smooth function approximation, but by contrast, a small spread value can result in numerical problems (Lee and Ko, 2009;Suchacz and (Ghoreishi and Heidari, 2013), so these variables were chosen to optimize the ANN structure by the GA program. Based on the result of this study, the optimum models were obtained with the hidden layer consisting of 9 neurons compared with the results of previous studies, which varied from 10 to 22 neurons (Bagheri et al, 2014;Han and Qiao, 2012). The best transfer function for the hidden layer was found to be a hyperbolic tangent sigmoid function while the best transfer function for the output layer was a linear one.…”

“…Fig. 3 illustrates that the GA Verification of a model is substantiating that the model is transformed from one form into another with sufficient accuracy (Bagheri et al, 2014). Model verification deals with building the A c c e p t e d M a n u s c r i p t 24 model right, and an accurate verification is required for the proper use of models in practical applications (Bagheri et al, 2014;Luccarini et al, 2010).…”

“…Fig. 4 shows the regression lines for the train and test data sets for SVI models by the (Bagheri et al, 2014). Additionally, a way to measure the predictive capability of a model is to test it on a set of data not used in the simulation process (Gernaey et al, 2004).…”

Mutual information based weight initialization method for sigmoidal feedforward neural networks

“…ETP is one of the main indicators for wastewater treatment which is time-consuming to measure. So predicting ETP with other indicators, which are easy to measure, is a simple and fast method [41][42][43]. To test the effectiveness of MIWI, we applied our method in predicting ETP.…”

Determination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network method

“…Such structures are processing structures that calculate the weight of connections on the system. In recent years, artificial neural network technique is used in many different areas, and quite successful results are obtained even in complex problems (Amanatiadis et al 2014;Bagheri et al 2014;Das et al 2015;Falamaki 2013;Farah et al 2011;Negarestani et al 2002;Otağ et al 2015;Raza et al 2012;Vega-Carrillo et al 2007;Zjavka 2014). The purpose of ANN method is making proper predictions for samples never seen before by using known samples collected before or previously measured results of the region.…”