Using fuzzy inference system to improve neural network for predicting hospital wastewater treatment plant effluent

Modeling of Biological Water and Wastewater Treatment Processes Using Artificial Neural Networks

“…It has been found that adaptive neuro fuzzy inference system statistically outperforms ANN in terms of effluent prediction. The application of ANN and fuzzy logic including linguistic expression of membership functions can overcome the limitations of traditional NN and increase the prediction performance [48].…”

Dynamic Fuzzy Neural-Network Model for Estimating Heavy Metal Concentration in Rice Using Spectral Indices and Environmental Parameters

“…Generally, the root mean square error (RMSE) and absolute percent error (APE) have been used to measure the performance of DFNN (Jang, 1993;Pai et al, 2009). In this study, the parameters were: (i) RMSE ; (ii) APE; and (iii) the correlation coefficient ( 2 R) .…”

Influential Parameters on Biomethane Generation in Anaerobic Wastewater Treatment Plants

“…Regarding the maximum coefficient of correlation (R) and the minimum mean absolute percentage errors (MAPE) of the predictions, the developed model showed a satisfactory performance in comparison with the pure ANN models. Therefore, the model developed could be recommended in order to optimize design considerations of the treatment process (Pai et al, 2009 (Zhu et al, 1998), optimal control of a wastewater treatment process integrated with PCA (Choi and Park, 2001), Kohonen Self-Organizing Feature Maps (KSOFM) to analyze the process data of municipal wastewater treatment plant (Timothy Hong et al, 2003), Unsupervised networks for modeling the wastewater treatment process (Garcia and Gonzalez, 2004;Hong and Bhamidimarri, 2003;Cinar, 2005), Grey Model ANN (GM-ANN) to predict suspended solids (SS) and COD of hospital wastewater treatment reactor effluents (Pai, 2007), on-line monitoring of a reactor (Luccarini, 2010 (Chen, 2003), control and supervise the submerged biofilm wastewater treatment reactor , modeling the nonlinear relationships between the removal rate of pollutants and their chemical dosages in a paper mill wastewater treatment plant Table 5 summarizes the aforementioned models together with the advantages and drawbacks which might be considered for selection in applied projects and utilization in industrial scales. As observed the most extensively used model is ANN.…”