- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Annual Issues ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
BioMed Research International
Volume 2013 (2013), Article ID 463401, 9 pages
Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia
1Core Group Pollution Prevention and Resource Recovery, Department of Environmental Engineering and Water Technology, UNESCO-IHE Institute for Water Education, P.O. Box 3015, 2601 DA Delft, The Netherlands
2Chemical Engineering Laboratory, Faculty of Sciences, University of La Coruña, Rúa da Fraga 10, 15008 La Coruña, Spain
3Department of Civil and Environmental Engineering, University of Ulsan, P.O. Box 18, Ulsan 680-749, Republic of Korea
Received 7 August 2013; Accepted 9 September 2013
Academic Editor: Kannan Pakshirajan
Copyright © 2013 Eldon R. Rene et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- F.-K. Huang, G. S. Wang, and Y. L. Tsai, “Rainfall reliability evaluation for stability of municipal solid waste landfills on slope,” Mathematical Problems in Engineering, vol. 2013, Article ID 653282, 10 pages, 2013.
- J. H. Kim, E. R. Rene, and H. S. Park, “Performance of an immobilized cell biofilter for ammonia removal from contaminated air stream,” Chemosphere, vol. 68, no. 2, pp. 274–280, 2007.
- J. H. Kim, E. R. Rene, and H. S. Park, “Biological oxidation of hydrogen sulfide under steady and transient state conditions in an immobilized cell biofilter,” Bioresource Technology, vol. 99, no. 3, pp. 583–588, 2008.
- C. Kennes and M. C. Veiga, “Fungal biocatalysts in the biofiltration of VOC-polluted air,” Journal of Biotechnology, vol. 113, no. 1-3, pp. 305–319, 2004.
- Ó. J. Prado, M. C. Veiga, and C. Kennes, “Treatment of gas-phase methanol in conventional biofilters packed with lava rock,” Water Research, vol. 39, no. 11, pp. 2385–2393, 2005.
- E. R. Rene, D. V. S. Murthy, and T. Swaminathan, “Performance evaluation of a compost biofilter treating toluene vapours,” Process Biochemistry, vol. 40, no. 8, pp. 2771–2779, 2005.
- E. R. Rene, M. Montes, M. C. Veiga, and C. Kennes, “Styrene removal from polluted air in one and two-liquid phase biotrickling filter: steady and transient-state performance and pressure drop control,” Bioresource Technology, vol. 102, no. 13, pp. 6791–6800, 2011.
- F. J. Álvarez-Hornos, C. Gabaldón, V. Martínez-Soria, M. Martín, P. Marzal, and J. M. Penya-roja, “Biofiltration of ethylbenzene vapours: influence of the packing material,” Bioresource Technology, vol. 99, no. 2, pp. 269–276, 2008.
- C. Kennes and M. C. Veiga, “Conventional Biofilters,” in Bioreactors for Waste Gas Treatment, C. Kennes and M. C. Veiga, Eds., pp. 47–98, Kluwer Academic, Dodrecht, The Netherlands, 2001.
- B. M. Langolf and G. T. Kleinheinz, “A lava rock-based biofilter for the treatment of alpha-pinene,” Bioresource Technology, vol. 97, no. 15, pp. 1951–1958, 2006.
- R. A. Pandey, K. V. Padoley, S. S. Mukherji et al., “Biotreatment of waste gas containing pyridine in a biofilter,” Bioresource Technology, vol. 98, no. 12, pp. 2258–2267, 2007.
- Y.-C. Chung, C. Huang, and C.-P. Tseng, “Biodegradation of hydrogen sulfide by a laboratory-scale immobilized Pseudomonas putida CH11 biofilter,” Biotechnology Progress, vol. 12, no. 6, pp. 773–778, 1996.
- Y.-C. Chung and C. Huang, “Biotreatment of ammonia in air by an immobilized Nitrosomonas europaea biofilter,” Environmental Progress, vol. 17, no. 2, pp. 70–76, 1998.
- Y.-C. Chung, C. Huang, and C.-P. Tseng, “Operation optimization of Thiobacillus thioparus CH11 biofilter for hydrogen sulfide removal,” Journal of Biotechnology, vol. 52, no. 1, pp. 31–38, 1996.
- M. A. Deshusses, G. Hamer, and I. J. Dunn, “Behavior of biofilters for waste air biotreatment. 1. Dynamic model development,” Environmental Science and Technology, vol. 29, no. 4, pp. 1048–1058, 1995.
- Y. Jin, M. C. Veiga, and C. Kennes, “Performance optimization of the fungal biodegradation of α-pinene in gas-phase biofilter,” Process Biochemistry, vol. 41, no. 8, pp. 1722–1728, 2006.
- S. P. P. Ottengraf and A. H. C. Van Den Oever, “Kinetics of organic compound removal from waste gases with a biological filter,” Biotechnology and Bioengineering, vol. 25, no. 12, pp. 3089–3102, 1983.
- Z. Shareefdeen, B. C. Baltzis, Y.-S. Oh, and R. Bartha, “Biofiltration of methanol vapor,” Biotechnology and Bioengineering, vol. 41, no. 5, pp. 512–524, 1993.
- P. Saravanan, K. Pakshirajan, and P. Saha, “Batch growth kinetics of an indigenous mixed microbial culture utilizing m-cresol as the sole carbon source,” Journal of Hazardous Materials, vol. 162, no. 1, pp. 476–481, 2009.
- J.-H. Kim, X. Guo, S. K. Behera, and H.-S. Park, “A unified model of ammonium oxidation rate at various initial ammonium strength and active ammonium oxidizer concentrations,” Bioresource Technology, vol. 100, no. 7, pp. 2118–2123, 2009.
- S. K. Behera, J.-H. Kim, X. Guo, and H.-S. Park, “Adsorption equilibrium and kinetics of polyvinyl alcohol from aqueous solution on powdered activated carbon,” Journal of Hazardous Materials, vol. 153, no. 3, pp. 1207–1214, 2008.
- E. R. Rene and M. B. Saidutta, “Prediction of water quality indices by regression analysis and artificial neural networks,” International Journal of Environmental Research, vol. 2, no. 2, pp. 183–188, 2008.
- B. Guo, D. Li, C. Cheng, Z.-A. Lü, and Y. Shen, “Simulation of biomass gasification with a hybrid neural network model,” Bioresource Technology, vol. 76, no. 2, pp. 77–83, 2001.
- D. Hanbay, I. Turkoglu, and Y. Demir, “Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks,” Expert Systems with Applications, vol. 34, no. 2, pp. 1038–1043, 2008.
- C. E. Romero and J. Shan, “Development of an artificial neural network-based software for prediction of power plant canal water discharge temperature,” Expert Systems with Applications, vol. 29, no. 4, pp. 831–838, 2005.
- M. A. Haider, K. Pakshirajan, A. Singh, and S. Chaudhry, “Artificial neural network-genetic algorithm approach to optimize media constituents for enhancing lipase production by a soil microorganism,” Applied Biochemistry and Biotechnology, vol. 144, no. 3, pp. 225–235, 2008.
- A. Elías, G. Ibarra-Berastegi, R. Arias, and A. Barona, “Neural networks as a tool for control and management of a biological reactor for treating hydrogen sulphide,” Bioprocess and Biosystems Engineering, vol. 29, no. 2, pp. 129–136, 2006.
- E. R. Rene, S. M. Maliyekkal, L. Philip, and T. Swaminathan, “Back-propagation neural network for performance prediction in trickling bed air biofilter,” International Journal of Environment and Pollution, vol. 28, no. 3-4, pp. 382–401, 2006.
- E. R. Rene, M. Estefanía López, M. C. Veiga, and C. Kennes, “Neural network models for biological waste-gas treatment systems,” New Biotechnology, vol. 29, no. 1, pp. 56–73, 2011.
- I. Chairez, I. García-Peña, and A. Cabrera, “Dynamic numerical reconstruction of a fungal biofiltration system using differential neural network,” Journal of Process Control, vol. 19, no. 7, pp. 1103–1110, 2009.
- E. R. Rene, J. H. Kim, and H. S. Park, “An intelligent neural network model for evaluating performance of immobilized cell biofilter treating hydrogen sulphide vapors,” International Journal of Environmental Science and Technology, vol. 5, no. 3, pp. 287–296, 2008.
- E. R. Rene, J. H. Kim, and H. S. Park, “Immobilized cell biofilter: results of performance and neural modeling strategies for NH3 vapor removal from waste gases,” Aerosol and Air Quality Research, vol. 9, no. 3, pp. 379–384, 2009.
- S. C. Chukwu and A. N. Nwachukwu, “Analysis of some meteorological parameters using artificial neural network method for Makurdi, Nigeria,” African Journal of Environmental Science and Technology, vol. 6, pp. 182–188, 2012.
- D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning representations by back-propagating errors,” Nature, vol. 323, no. 6088, pp. 533–536, 1986.
- H. R. Maier and G. C. Dandy, “The effect of internal parameters and geometry on the performance of back-propagation neural networks: an empirical study,” Environmental Modelling and Software, vol. 13, no. 2, pp. 193–209, 1998.
- H. R. Maier and G. C. Dandy, “Neural network based modelling of environmental variables: a systematic approach,” Mathematical and Computer Modelling, vol. 33, no. 6-7, pp. 669–682, 2001.
- K. Hornik, M. Stinchcombe, and H. White, “Multilayer feedforward networks are universal approximators,” Neural Networks, vol. 2, no. 5, pp. 359–366, 1989.
- S. P. P. Ottengraf, “Exhaust gas purification,” in Biotechnology: A Comprehensive Treatise, H. J. Rhem and G. Reed, Eds., vol. 8, pp. 425–452, VCH, Weinheim, Germany, 1986.
- G. R. Chegini, J. Khazaei, B. Ghobadian, and A. M. Goudarzi, “Prediction of process and product parameters in an orange juice spray dryer using artificial neural networks,” Journal of Food Engineering, vol. 84, no. 4, pp. 534–543, 2008.
- J. M. Zurada, A. Malinowski, and I. Cloete, “Sensitivity analysis for minimization of input data dimension for feedforward neural network,” in Proceedings of the IEEE International Symposium on Circuits and Systems, pp. 447–450, June 1994.