Adaptive network fuzzy inference system modeling for the input selection and prediction of anaerobic digestion effluent quality

Applied Mathematical Modelling

Volumn 35, Issue 8, 2011, Pages 3821-3832

  Erdirencelebi, Dilek ^a   Yalpir, Sukran ^a  

^a SELCUK UNIVERSITY   (Turkey)

Author keywords

Anaerobic treatment; ANFIS; Dairy wastewater; Modeling; UASBR

Indexed keywords

ANAEROBIC TREATMENTS; ANFIS; DAIRY WASTEWATER; MODELING; UASBR;

CONTROL SYSTEMS; DIGESTIVE SYSTEM; EFFLUENT TREATMENT; EFFLUENTS; FORECASTING; FUZZY INFERENCE; FUZZY SYSTEMS; WASTEWATER; WASTEWATER TREATMENT; WATER QUALITY;

ANAEROBIC DIGESTION;

EID: 79955093435     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2011.02.015     Document Type: Article

References (37)

1. Husain A. Mathematical models of the kinetics of anaerobic digestion - a selected review. Biomass Bioener. 1998, 14:561-571.
2. Lata K., Kansal A., Balakrishnan M., Rajeshwari K.V., Kishore V.V.N. Assessment of biomethanation potential of selected industrial organic effluents in India. Resour. Conserv. Recycl. 2002, 35:147-161.
3. Kassab G., Halalsheh M., Klapwijk A., Fayyad M., van Lier J.B. Sequential anaerobic-aerobic treatment for domestic wastewater - a review. Bioresour. Technol. 2010, 101:3299-3310.
4. McCarthy J.F. Changing to gray: decentralization and the emergence of volatile socio-legal configurations in Central Kalimantan, Indonesia. World Dev. 2004, 32:1199-1223.
5. Sujaritpong S., Nitivattananon V. Factors influencing wastewater management performance: case study of housing estates in suburban Bangkok, Thailand. J. Environ. Manage. 2009, 90:455-465.
6. Anderson G.K., Yang G. Determination of bicarbonate and total volatile acid concentration in anaerobic digesters using a simple titration. Water Environ. Res. 1992, 64:53-59.
7. Demirel B., Yenigun O., Onay T. Anaerobic treatment of dairy wastewater: a review. Process Biochem. 2005, 40:2583-2595.
8. Yu H.Q., Fang H.H.P. Acidification of mid- and high-strength dairy wastewaters. Water Res. 2001, 35:3697-3705.
9. Omil F., Garrido J.M., Arrojo B., Mendez R. Anaerobic filter reactor performance for the treatment of complex dairy wastewater at industrial scale. Water Res. 2003, 37:4099-4108.
10. Gavala H.N., Kopsinis H., Skiadas I.V., Stamatelatou K., Lyberatos G. Treatment of dairy wastewater using an upflow anaerobic sludge blanket reactor. J. Agric. Eng. Res. 1999, 73:59-63.
11. Sayed S., Zanden J., Wijiffels R., Lettinga G. Anaerobic degradation of the various fractions of slaughterhouse wastewater. Biol. Wastes 1988, 23:117-142.
12. Perle M., Kimchie S.H., Shwlef G. Some biochemical aspects of the anaerobic degradation of dairy wastewater. Water Res. 1995, 29:1549-1554.
13. Rinzema A., van Veen H., Lettinga G. Anaerobic digestion of triglyceride emulsions in expanded granular sludge bed reactors with modified sludge separators. Environ. Technol. 1993, 14:423-432.
14. Civelekoglu G., Perendeci A., Yigit N.O., Kitis M. Modeling carbon and nitrogen removal in an industrial wastewater treatment plant using an adaptive network-based fuzzy inference system. Clean-Soil Air Water 2007, 35:617-625.
15. Murnleitner E., Becker T.M., Delgado A. State detection and control of overloads in the anaerobic wastewater treatment using fuzzy logic. Water Res. 2002, 36:201-211.
16. Hamed M.M., Khalafallah M.G., Hassanien E.A. Prediction of wastewater treatment plant performance using artificial neural networks. Environ. Model. Software 2004, 19:919-928.
17. Mjalli F.S., Al-Asheh S., Alfadala H.E. Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance. J. Environ. Manage. 2007, 83:329-338.
18. P. Piero, Bonissone adaptive neural fuzzy inference systems (ANFIS): analysis and applications, 2002. http://www.rpi.edu/~bonisp/fuzzy-course/Papers-pdf/anfis.rpi04.pdf.
19. Yazdi H.S., Hosseini S.E., Yazdi M.S. Neuro-fuzzy based constraint programming. Appl. Math. Model. 2010, 34:3547-3559.
20. Tay J.H., Zhang X. A fast predicting neural fuzzy model for high-rate anaerobic wastewater treatment systems. Water Res. 2000, 34:2849-2860.
21. Tay J.H., Zhang X. Neural fuzzy modeling of anaerobic biological wastewater treatment systems. J. Environ. Eng. ASCE 1999, 125:1149-1159.
22. Perendeci A., Arslan S., Celebi S., Tanyolac A. Prediction of effluent quality of an anaerobic treatment plant under unsteady state through ANFIS modeling with on-line input variables. Chem. Eng. J. 2008, 145:78-85.
23. Perendeci A., Arslan S., Tanyolac A., Celebi S. Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state. Bioresour. Technol. 2009, 100:4579-4587.
24. Yilmaz M. Adaptive network based on fuzzy inference system estimates of geoid heights interpolation. Scientific Res. Essays 2010, 5:2148-2154.
25. S. Yalpir, G. Ozkan, The Development of a Residential Real-Estate Valuation Model with ANFIS Approach, 1st International Symposium on Computing in Science & Engineering, Gediz University, Izmir, 2010.
26. Vassilopoulos A.P., Bedi R. Adaptive neuro-fuzzy inference system in modelling fatigue life of multidirectional composite laminates. Comput. Mat. Sci. 2008, 43:1086-1093.
27. Dong M., Wang N. Adaptive network-based fuzzy inference system with leave-one-out cross-validation approach for prediction of surface roughness. Appl. Math. Model. 2011, 35:1024-1035.
28. Buyukbingol E., Sisman A., Akyildiz M., Alparslan F.N., Adejare A. Adaptive neuro-fuzzy inference system (ANFIS): a new approach to predictive modeling in QSAR applications: a study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists. Bioorg. Med. Chem. 2007, 15:4265-4282.
29. Wei M., Bai B., Sung A.H., Liu Q., Wang J., Cather M.E. Predicting injection profiles using ANFIS. Inform. Sci. 2007, 177:4445-4461.
30. Mellit A., Kalogirou S.A. ANFIS-based modelling for photovoltaic power supply system: a case study. Renew. Energy 2011, 36:250-258.
31. Carrasco E.F., Rodríguez J., Puñal A., Roca E., Lema J.M. Diagnosis of acidification states in an anaerobic wastewater treatment plant using a fuzzy-based expert system. Cont. Eng. Pract. 2004, 12:59-64.
32. Carlos-Hernandez S., Sanchez E.N., Béteau J.F. Fuzzy observers for anaerobic WWTP: development and implementation. Cont. Eng. Pract. 2009, 17:690-702.
33. Polit M., Estaben M., Labat P. A fuzzy model for an anaerobic digester, comparison with experimental results. Eng. App. Art. Intel. 2002, 15:385-390.
34. Ilter Turkdogan-Aydi{dotless}nol F., Yetilmezsoy Kaan A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater. J. Hazard. Mat. 2010, 182:460-471.
35. Genovesi A., Harmand J., Steye J.-P. A fuzzy logic based diagnosis system for the on-line supervision of an anaerobic digestor pilot-plant. Biochem. Eng. J. 1999, 3:171-183.
36. Erdirencelebi D. Treatment of high-fat-containing dairy wastewater in a sequential UASBR system: influence of recycle. J. Chem. Technol. Biotechnol. 2010, 10.1002/jctb.2546.
37. APHA, Standard Methods for the Examination of Water and Wastewater, American Public Health Association, Washington, DC, 2005.