LAUSR

In this study three modeling approaches consisting Modified Stover-Kincannon, multilayer perceptron neural network (MLPANN) and B-Spline quasi interpolation were applied in order to predict effluent of up-flow anaerobic sludge blanket (UASB) reactor and also to find the reaction kinetics. At first run, the average total chemical oxygen demand (TCOD) removal efficiency was 48.3% with hydraulic retention time (HRT) of 26 h and 63.8% with HRT of 37 h, at OLR of 0.77–1.66 kg TCOD/m3 d. At the second run, UASB reactor operated with OLR of 1.94–3.1 kg TCOD/m3 d and achieved the average TCOD removal efficiency of 64.74 and 72.48% with HRT of 26 and 37 h, respectively. The Modified Stover-Kincannon performed well in terms of kinetic determination with a high value of regression coefficient over 0.98. The B-Spline quasi interpolation and MLPANN indicated a great fit for effluent prediction with average R of 0.9984 and 0.9986, and MSE of 157.6050 and 129.7796, respectively; however, they gave no information about reactions occurred in the system.