Modeling of submerged membrane bioreactor treating cheese whey wastewater by artificial neural network

Cinar O., Hasar H., Kinaci C.

JOURNAL OF BIOTECHNOLOGY, vol.123, no.2, pp.204-209, 2006 (Peer-Reviewed Journal) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 123 Issue: 2
  • Publication Date: 2006
  • Doi Number: 10.1016/j.jbiotec.2005.11.002
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.204-209


A submerged membrane bioreactor receiving cheese whey was modeled by artificial neural network and its performance over a period of 100 days at different solids retention times was evaluated with this robust tool. A cascade-forward network was used to model the membrane bioreactor and normalization was used as a preprocessing method. The network was fed with two subsets of operational data, with two-thirds being used for training and one-third for testing the performance of the artificial neural network. The training procedure for effluent chemical oxygen demand (COD), ammonia, nitrate and total phosphate concentrations was very successful and a perfect match was obtained between the measured and the calculated concentrations. The results of the confirmation (or testing) procedure for effluent ammonia and nitrate concentrations were very successful; however, the results of the confirmation procedure for effluent COD and total phosphate concentrations were only satisfactory. (c) 2005 Elsevier B.V. All rights reserved.