naa a22 4500 510821421 CHVBK 20180411083534.0 cr unu---uuuuu 180411e20130201xx s 000 0 eng 10.1007/s11814-012-0128-7 doi (NATIONALLICENCE)springer-10.1007/s11814-012-0128-7 Neural network prediction of fluidized bed bioreactor performance for sulfide oxidation [Elektronische Daten] [Varsha Midha, Mithilesh Jha, Apurba Dey] Sulfide oxidation rate of a fluidized bed bioreactor was predicted using ANN, with upflow velocity, hydraulic retention time, reactor operation time and pH given as input. The reactor was fed with 100mg/L synthetic sulfide wastewater after biofilm formation on nylon support particles. Feedforward neural network model was prepared using 81 data sets, of which 63 were used for training and 18 for testing in a three-way cross validation. Prediction performance of the network was evaluated by calculating the percent error of each data set and mean square error for test data set in three partitions. The mean square error for test data set was 5.55, 4.08 and 2.30 for partition 1, partition 2 and partition 3, respectively. The predicted sulfide oxidation values correlated with the experimental values and a correlation coefficient of 0.96, 0.97 and 0.98 was obtained for partition 1, partition 2 and partition 3, respectively. Korean Institute of Chemical Engineers, Seoul, Korea, 2012 FBBR nationallicence Mean Square Error nationallicence Neural Network nationallicence Sulfide nationallicence Sulfur nationallicence Midha Varsha Department of Chemical Engineering, National Institute of Technology, 144 011, Jalandhar, India aut Jha Mithilesh Department of Chemical Engineering, National Institute of Technology, 144 011, Jalandhar, India aut Dey Apurba Department of Biotechnology, National Institute of Technology, Durgapur, India aut Korean Journal of Chemical Engineering Springer US; http://www.springer-ny.com 30/2(2013-02-01), 385-391 0256-1115 30:2<385 2013 30 11814 https://doi.org/10.1007/s11814-012-0128-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11814-012-0128-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Midha Varsha Department of Chemical Engineering, National Institute of Technology, 144 011, Jalandhar, India aut NATIONALLICENCE 700 1- Jha Mithilesh Department of Chemical Engineering, National Institute of Technology, 144 011, Jalandhar, India aut NATIONALLICENCE 700 1- Dey Apurba Department of Biotechnology, National Institute of Technology, Durgapur, India aut NATIONALLICENCE 773 0- Korean Journal of Chemical Engineering Springer US; http://www.springer-ny.com 30/2(2013-02-01), 385-391 0256-1115 30:2<385 2013 30 11814 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer