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SAINLEZ Matthieu

Main Referenced Co-authors
Heyen, Georges (7)
Absil, Pierre-Antoine (1)
Lafourcade, Sébastien (1)
Lumen, Philippe (1)
Teschendorff, Andrew E. (1)
Main Referenced Keywords
data mining (2); Dynamic approach (1); gene expression (1); independent component analysis (1); Kraft recovery boiler (1);
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (9)
Computer science (2)

Publications (total 11)

The most cited

13 citations (Scopus®)

Sainlez, M., & Heyen, G. (2011). Recurrent neural network prediction of steam production in a Kraft recovery boiler. In M. C. G. E.N. Pistikopoulos & A. C. Kokossis (Eds.), 21st European Symposium on Computer Aided Process Engineering (pp. 1784 - 1788). Elsevier. doi:10.1016/B978-0-444-54298-4.50135-5 https://hdl.handle.net/10993/16296

Sainlez, M., & Heyen, G. (2013). Comparison of Supervised Learning Techniques for Atmospheric Pollutant Monitoring in a Kraft Pulp Mill. Journal of Computational and Applied Mathematics, 246, 329--334. doi:10.1016/j.cam.2012.06.026
Peer Reviewed verified by ORBi

Sainlez, M., & Heyen, G. (27 January 2012). Machine learning techniques for atmospheric pollutant monitoring [Poster presentation]. PhD day ENVITAM-GEPROC, Gembloux, Belgium.

Sainlez, M. (15 November 2011). Comparison of Machine Learning techniques for atmospheric pollutant monitoring: a Kraft pulp mill case study [Paper presentation]. Fifth International Conference on Advanced COmputational Methods in ENgineering (ACOMEN 2011), Liège, Belgium.

Sainlez, M., & Heyen, G. (November 2011). Comparison of Machine Learning techniques for atmospheric pollutant monitoring in a Kraft pulp mill [Paper presentation]. ACOMEN 2011 - International Conference on Advanced COmputational Methods in ENgineering, Liège, Belgium.

Sainlez, M., Heyen, G., & Lumen, P. (27 May 2011). Approche neuronale dynamique pour la prédiction de polluants atmosphériques: application à l'industrie papetière [Paper presentation]. 43èmes Journées de Statistiques SFDS, Gammarth- Tunis, Tunisia.

Sainlez, M. (27 May 2011). Dynamic neural network approach for atmospheric pollutant prediction: A pulp mill case study [Paper presentation]. 43èmes Journées de Statistique de la SFdS, Gammarth - Tunis, Tunisia.

Sainlez, M., Heyen, G., & Lafourcade, S. (2011). Supervised learning for a Kraft recovery boiler: a data mining approach with Random Forests. In D. Favrat & F. Maréchal (Eds.), ECOS 2010 Volume IV (Power plants and Industrial processes).
Peer reviewed

Sainlez, M., & Heyen, G. (2011). Recurrent neural network prediction of steam production in a Kraft recovery boiler. In M. C. G. E.N. Pistikopoulos & A. C. Kokossis (Eds.), 21st European Symposium on Computer Aided Process Engineering (pp. 1784 - 1788). Elsevier. doi:10.1016/B978-0-444-54298-4.50135-5
Peer reviewed

Sainlez, M., & Heyen, G. (2010). Performance monitoring of an industrial boiler: classification of relevant variables with Random Forests. In S. Pierucci & G. B. Ferraris (Eds.), 20th European Symposium on Computer Aided Process Engineering (pp. 403 - 408). Elsevier. doi:10.1016/S1570-7946(10)28068-9
Peer reviewed

Sainlez, M., Absil, P.-A., & Teschendorff, A. E. (2009). Gene expression data analysis using spatiotemporal blind source separation. In M. Verleysen (Ed.), ESANN'2009 proceedings, European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (pp. 159-163). Evere, Belgium: d-side.
Peer reviewed

Sainlez, M. (2009). Techniques avancées de data mining pour l’optimisation énergétique [Poster presentation]. Journée scientifique Inter Hautes Ecoles, Namur, Belgium.

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