- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- 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
Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 846321, 9 pages
Modelling of Water Quality: An Application to a Water Treatment Process
1Department of Environmental Science, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
2Finnsugar Ltd., Sokeritehtaantie 20, 02460 Kantvik, Finland
Received 10 October 2011; Revised 19 December 2011; Accepted 25 December 2011
Academic Editor: Cheng-Jian Lin
Copyright © 2012 Petri Juntunen 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.
- World Health Organization, Guidelines for drinking-water quality, vol. 1, Recommendations, 3rd edition, 2006.
- R. D. Letterman, Ed., Water Quality & Treatment, Handbook of Community Water Supplies, AWWA, 1999.
- A. Campell, “The role of aluminium and copper on neuroinflammation and Alzheimer’s disease,” Journal of Alzheimer’s Disease, vol. 10, pp. 165–172, 2006.
- J. E. Van Benschoten and J. K. Edzwald, “Chemical aspects of coagulation using aluminum salts - I. Hydrolytic reactions of alum and polyaluminum chloride,” Water Research, vol. 24, no. 12, pp. 1519–1526, 1990.
- J. E. Van Benschoten and J. K. Edzwald, “Chemical aspects of coagulation using aluminum salts - II. Coagulation of fulvic acid using alum and polyaluminum chloride,” Water Research, vol. 24, no. 12, pp. 1527–1535, 1990.
- C. Huang and H. Shiu, “Interactions between alum and organics in coagulation,” Colloids and Surfaces A, vol. 113, no. 1-2, pp. 155–163, 1996.
- P. Juntunen, M. Liukkonen, M. Lehtola, and Y. Hiltunen, “Cluster analysis of a water treatment process by self-organizing maps,” in Proceedings of the 8th IWA Symposium on Systems Analysis and Integrated Assessment, E. Ayesa and I. Rodríquez-Roda, Eds., pp. 553–558, WATERMATEX, 2011.
- P. Juntunen, M. Liukkonen, M. Lehtola, and Y. Hiltunen, “Dynamic modelling approach for detecting turbidity in drinking water,” in Proceedings of the 52nd International Conference of Scandinavian Simulation Society, E. Dahlquist, Ed., 2011.
- C. W. Baxter, Q. Zhang, S. J. Stanley, R. Shariff, R. R. T. Tupas, and H. L. Stark, “Drinking water quality and treatment: the use of artificial neural networks,” Canadian Journal of Civil Engineering, vol. 28, supplement 1, pp. 26–35, 2001.
- D. N. Thomas, S. J. Judd, and N. Fawcett, “Flocculation modelling: a review,” Water Research, vol. 33, no. 7, pp. 1579–1592, 1999.
- H. R. Maier, N. Morgan, and C. W. K. Chow, “Use of artificial neural networks for predicting optimal alum doses and treated water quality parameters,” Environmental Modelling and Software, vol. 19, no. 5, pp. 485–494, 2004.
- S. Haykin, Neural Networks and Learning Machines, Pearson Education, Upper Saddle River, NJ, USA, 3rd edition, 2009.
- P. Kadlec, B. Gabrys, and S. Strandt, “Data-driven Soft Sensors in the process industry,” Computers and Chemical Engineering, vol. 33, no. 4, pp. 795–814, 2009.
- M. R. G. Meireles, P. E. M. Almeida, and M. G. Simões, “A comprehensive review for industrial applicability of artificial neural networks,” IEEE Transactions on Industrial Electronics, vol. 50, no. 3, pp. 585–601, 2003.
- M. Heikkinen, H. Poutiainen, M. Liukkonen, T. Heikkinen, and Y. Hiltunen, “Self-organizing maps in the analysis of an industrial wastewater treatment process,” Mathematics and Computers in Simulation, vol. 82, no. 3, pp. 450–459, 2011.
- A. M. Kalteh, P. Hjorth, and R. Berndtsson, “Review of the self-organizing map (SOM) approach in water resources: analysis, modelling and application,” Environmental Modelling and Software, vol. 23, no. 7, pp. 835–845, 2008.
- H. R. Maier and G. C. Dandy, “Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications,” Environmental Modelling and Software, vol. 15, no. 1, pp. 101–124, 2000.
- M. S. Gibbs, G. C. Dandy, and H. R. Maier, “Calibration and optimization of the pumping and disinfection of a real water supply system,” Journal of Water Resources Planning and Management, vol. 136, no. 4, Article ID 023003QWR, pp. 493–501, 2010.
- C. W. Baxter, S. J. Stanley, and Q. Zhang, “Development of a full-scale artificial neural network model for the removal of natural organic matter by enhanced coagulation,” Journal of Water Supply: AQUA, vol. 48, no. 4, pp. 129–136, 1999.
- J. L. Giraudel and S. Lek, “A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination,” Ecological Modelling, vol. 146, no. 1–3, pp. 329–339, 2001.
- P. J. Werbos, Beyond regression: new tools for prediction and analysis in the behavioral sciences, Doctoral thesis, Harvard University, Cambridge, Mass, USA, 1974.
- A. K. Jain, R. P. W. Duin, and J. Mao, “Statistical pattern recognition: a review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4–37, 2000.
- A. L. Blum and P. Langley, “Selection of relevant features and examples in machine learning,” Artificial Intelligence, vol. 97, no. 1-2, pp. 245–271, 1997.
- I. Guyon and A. Elisseeff, “An introduction to variable and feature selection,” Journal of Machine Learning Research, vol. 3, pp. 1157–1182, 2003.
- H. Liu and H. Motoda, Eds., Computational Methods of Feature Selection, Chapman & Hall, Boca Raton, Fla, USA, 2008.
- A. W. Whitney, “Direct method of nonparametric measurement selection,” IEEE Transactions on Computers, vol. C-20, no. 9, pp. 1100–1103, 1971.
- D. J. C. MacKay, “A practical bayesian framework for backpropagation networks,” Neural Computation, vol. 4, no. 3, pp. 448–472, 1992.