The Estimation of Substrate Concentrations in Sequencing Batch Reactor by using Artificial Intelligence Methods

The aim of the study was the estimation of substrate concentrations at the end of reaction phase (Se, mg/l) which varying of Sf values (substrate concentrations at the end of filling phase, mg/l) and time (tr, h) depend on wastewater flow rate (Q, m3/h) in sequencing batch reactor (SBR) by using Neural Network and Adaptive Neuro Fuzzy Inference System (ANFIS) approaches. The main purpose of using these methods was rapidly access to true and certain solutions according to conventional mathematical methods. A performance method was developed to compare the applicable systems performances. Obtained data form each model were analyzed independently and error quantities of systems were calculated by comparing with prior mathematical method results. The error quantities for Neural Network method were %0.7 at test set and %0.02 at training set. In Adaptive Neuro Fuzzy Inference System (ANFIS), the error quantities were %0.9 and %0.03 in respect of test set and training set. Neural Network approach was turned out satisfactory with lower error quantities. But also each method was in practical level because of their low differences between the error quantities. Obtained results were evinced that these two approaches was rapidly accessed to the true and certain results instead of conventional mathematical methods.