UMR CNRS 7253

Thierry Denoeux
Thierry Denoeux
Thierry Denoeux
Thierry Denoeux
Thierry Denoeux

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Neural networks

  1. N. Valentin et T. Denoeux. Modélisation du procédé de coagulation en traitement d'eau potable à l'aide de réseaux de neurones artificiels In Actes des 14èmes Journées Information Eaux, Tome 1, pages 23-(1-11), Poitiers, 13-15 septembre 2000.
  2. T. J. Böhme, N. Valentin, C. S. Cox and T. Denoeux. Comparison of autoassociative neural networks and Kohonen maps for signal failure detection and reconstruction. In C. H. Dagli et al., editors, Intelligent Engineering Systems through Artificial Neural Networks 9 (Proc. of ANNIE'99), pages 637-644, ASME Press, Saint-Louis, 1999. pdf
  3. N. Valentin, F. Fotoohi and T. Denoeux. Modeling of coagulant dosing in a water treatment plant. Proc. of EANN'99, pages 165-170, Warsaw, September 1999. pdf
  4. N. Valentin, T. Denoeux and F. Fotoohi. A hybrid neural network based system for optimization of coagulant dosing in a water treatment plant. Proceedings of IJCNN'99, Washington D.C., July 1999. IEEE. pdf
  5. N. Gong, T. Denoeux and J.-L. Bertrand-Krajewski. Assessment of neural networks for solid transport modeling in sewer systems. 7th International Conference on Urban Storm Drainage, volume 2, pages 869-874, Hannover, September 9-13, 1996.
  6. N. Gong, X. Ding, T. Denoeux, M. Clément and J.-L. Bertrand-Krajewski. Stormnet: A neural network model for flow and pollutant transport in sewer systems during wet weather. In Water Environment Federation Specialty Conference, Urban wet weather pollution : controlling sewer overflows and stormwater runoff, Quebec City, Canada, June 16-19, 1996.
  7. M. Karouia, T. Denoeux, and R. Lengellé. Influence of weight initialization on multilayer perceptron performance. In International Conference of Artificial Neural Networks (ICANN'95), volume 1, pages 33-38, Paris, October 1995. EC2. pdf
  8. T. Trautmann and T. Denoeux. Comparison of dynamic feature map models for environmental monitoring. In Proceedings of ICNN'95, volume 1, pages 73-78, Perth, November 1995. IEEE. postscript
  9. M. Karouia, T. Denoeux, and R. Lengellé. Performance analysis of a MLP weight initialization algorithm. In Third European Symposium on Artificial Neural Networks (ESANN'95), pages 347-352, Brussels, April 1995. D facto publications. pdf
  10. N. Gong, T. Denoeux and J.-L. Bertrand-Krajewski. Neural networks for solid transport modeling in sewer systems during storm events. In Proceedings of the IAWQ Int. Conf. on sewer solids - Characteristics, movement, effect and control, Dundee, Scotland, September 1995.
  11. N. Gong, X. Ding, and T. Denoeux. Urban storm water pollution forecasting using recurrent neural networks. In A. B. Bulsari and S. Kallio (Eds), Engineering Applications of Artificial Neural Networks (Proc. of the International Conference EANN'95), pages 307-314, Helsinski, August 1995. Finnish Artificial Intelligence Society.
  12. J. M. Boisseau, B. Monier, O. Lefèvre, T. Denoeux and X. Ding. Prévision de trafic autoroutier par réseaux de neurones artificiels. In Les Systèmes Intelligents dans les Entreprises, Montpellier, Juin 1995, EC2.
  13. T. Trautmann and T. Denoeux. A constructive algorithm for S.O.M. applied to water quality monitoring. In C. H. Dagli, B. R. Fernández, J. Ghosh, and R. T. S. Kumara, editors, Intelligent Engineering Systems through artificial neural networks Vol. 4, pages 17-22. ASME Press, New-York, 1994.
  14. T. Trautmann and T. Denoeux. BungySOM: A constructive algorithm for self-organizing maps. In Neural Networks and their Applications, pages 445-452, Marseilles, France, December 1994. IUSM.
  15. M. Karouia, R. Lengellé, and T. Denoeux. Weight initialization in BP networks using discriminant analysis techniques. In Neural Networks and their Applications, pages 171-180, Marseilles, France, December 1994. IUSM.
  16. M. Karouia, R. Lengellé, and T. Denoeux. Performance comparison of two constructive algorithms for multilayer perceptrons. In C. H. Dagli, L. I. Burke, B. R. Fernandez, and J. Ghosh, editors, Intelligent Engineering Systems through artificial neural networks Vol. 3, pages 221-226. ASME Press, New-York, 1993.
  17. X. Ding, T. Denoeux, and F. Helloco. Tracking rain cells in radar images using multilayer neural networks. In S. Gielen and B. Kappen, editors, Proceedings of ICANN'93, pages 962-967. Springer-Verlag, London, 1993.
  18. T. Denoeux and R. Lengellé. Production rules generation and refinement in BP networks. In C. H. Dagli, L. I. Burke, and Y. C. Shin, editors, Intelligent Engineering Systems through artificial neural networks Vol. 2, pages 253-258. ASME Press, New-York, 1992. pdf
  19. T. Denoeux. Generation of symbolic rules in back-propagation networks. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks II, pages 711-714. North-Holland, Amsterdam, 1992.
  20. R. Lengellé and T. Denoeux. Optimizing multilayer networks layer per layer without back-propagation. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks II, pages 995-998. North-Holland, Amsterdam, 1992.
  21. H. Wiklicky, T. Denoeux, A. Lafuente, J. Olarte, S. Rementeria, and V. Walravens. A tripartite framework for artificial neural networks. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks II, pages 1031-1034. North-Holland, Amsterdam, 1992.
  22. R. Lengellé, Y. Hao, N. Schaltenbrand, and T. Denoeux. Ambiguity and distance rejection in multilayer neural networks. In C. H. Dagli, S. R. T. Kumara, and Y. C. Shin, editors, Intelligent Engineering Systems Through Artificial Neural Networks, pages 299-304, New-York, 1991. ASME Press.
  23. T. Denoeux, R. Lengellé, and S. Canu. Initialization of weights in a feedforward neural network using prototypes. In T. Kohonen, K. Mäkisara, O. Simula, and J. Kangas, editors, Artificial Neural Networks, pages 623-628, Amsterdam, 1991. North-Holland.

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