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

• Published in: Journal of biotechnology 2006-05, Vol.123 (2), p.204-209
• Main Authors: Çinar, Özer, Hasar, Halil, Kinaci, Cumali
• Format: Article
• Language: English
• Subjects: Algorithms; Ammonia; Artificial neural network; Bacteria, Anaerobic - metabolism; Biological and medical sciences; bioreactors; Bioreactors - microbiology; Biotechnology; Cascade-forward network; Cell Culture Techniques - methods; Cheese - microbiology; Cheese whey; chemical oxygen demand; Computer Simulation; food processing wastes; Fundamental and applied biological sciences. Psychology; Industrial Waste - prevention & control; mathematical models; Models, Biological; neural networks; nitrates; Oxygen - metabolism; phosphates; Submerged membrane bioreactor; submerged membrane bioreactors; wastewater treatment; Water Pollutants, Chemical - metabolism; Water Purification - methods
• ISSN: 0168-1656; 1873-4863
• DOI: 10.1016/j.jbiotec.2005.11.002

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.