<  Retour au portail Polytechnique Montréal

Documents dont l'auteur est "Labib, Richard"

Monter d'un niveau
Pour citer ou exporter [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Grouper par: Auteurs ou autrices | Date de publication | Sous-type de document | Aucun groupement
Aller à : B | C | D | H | K | L | P | R | S | Z
Nombre de documents: 32

B

Brault, J.-M., Labib, R., Perrier, M., & Stuart, P. R. (2011). Prediction of activated sludge filamentous bulking using ATP data and neural networks. Canadian Journal of Chemical Engineering, 89(4), 901-913. Lien externe

Bernier, M., Labib, R., Pinel, P., & Paillot, R. (2004). A Multiple load aggregation algorithm for annual hourly simulations of GCHP systems. HVAC and R Research, 10(4), 471-487. Lien externe

Birikundavyi, S., Labib, R., Trung, H. T., & Rousselle, J. (2002). Performance of Neural Networks in Daily Streamflow Forecasting. Journal of Hydrologic Engineering, 7(5), 392-398. Lien externe

C

Connolly, J.-F., & Labib, R. (2009). A multiscale scheme for approximating the Quantron's discriminating function. IEEE Transactions on Neural Networks, 20(8), 1254-1266. Lien externe

D

Denis, H. L., Alpaugh, M., Alvarez, C. P., Fenyi, A., Barker, R. A., Chouinard, S., Arrowsmith, C. H., Melki, R., Labib, R., Harding, R. J., & Cicchetti, F. (2023). Detection of antibodies against the huntingtin protein in human plasma. Cellular and Molecular Life Sciences, 80(2), 45 (11 pages). Lien externe

De Montigny, S., & Labib, R. (juillet 2011). Learning Algorithms for a Specific Configuration of the Quantron [Communication écrite]. International Joint Conference on Neural Networks (IJCNN 2011), San Jose, California. Lien externe

H

Hajlaoui, Y., Labib, R., Plante, J.-F., & Gamache, M. (2025). Backpropagation-based inference for spatial interpolation to estimate the blastability index in an open pit mine. Computers and Geosciences, 194, 15 pages. Lien externe

Hamel, É., & Labib, R. (2019). Modeling biological refractory periods and synaptic depression in an artificial neuron. Biomedical Physics & Engineering Express, 5(2), 025038 (16 pages). Lien externe

K

Kolus, A., Dube, P. A., Imbeau, D., Labib, R., & Dubeau, D. (2014). Estimating oxygen consumption from heart rate using adaptive neuro-fuzzy inference system and analytical approaches. Applied Ergonomics, 45(6), 1475-1483. Lien externe

L

Lamontagne-Proulx, J., St-Amour, I., Labib, R., Pilon, J., Denis, H. L., Cloutier, N., Roux-Dalvai, F., Vincent, A. T., Mason, S. L., Williams-Gray, C., Duchez, A.-C., Droit, A., Lacroix, S., Dupre, N., Langlois, M., Chouinard, S., Panisset, M., Barker, R. A., Boilard, E., & Cicchetti, F. (2019). Portrait of blood-derived extracellular vesicles in patients with Parkinson's disease. Neurobiology of Disease, 124, 163-175. Lien externe

Labib, R., & Montigny, S. (2016). Closed-Form Evaluation of Integrals Involving the Gamma Function. Communications in Statistics - Theory and Methods, 46(17), 8328-8342. Lien externe

L'Espérance, P.-Y., & Labib, R. (2013). Model of an Excitatory Synapse Based on Stochastic Processes. IEEE Transactions on Neural Networks and Learning Systems, 24(9), 1449-58. Lien externe

Labib, R., & De Montigny, S. (2012). On the learning potential of the approximated quantron. International Journal of Neural Systems, 22(3). Lien externe

Labib, R., & Khattar, K. (2010). Mlp Bilinear Separation. Neural Computing and Applications, 19(2), 305-315. Lien externe

Labib, R., & Assadi, R. (2007). Modified Multi-Layered Perceptron Applied to Packing and Covering Problems. Neural Computing and Applications, 16(2), 173-186. Lien externe

Labib, R., de Montigny, S., & Adadji, M. (2006). Le grand livre des lois : parcours dans le monde des probabilités. Lien externe

Labib, R., Audette, F., Fortin, A., & Assadi, R. (2005). Hardware implementation of a new artificial neuron. International Journal of Neural Systems, 15(6), 427-433. Lien externe

Labib, R. (2004). Closure to "Performance of Neural Networks in Daily Streamflow Forecasting" by S. Birikundavyi, R. Labib, H. T. Trung, and J. Rousselle. Journal of Hydrologic Engineering, 9(6), 557-558. Lien externe

Labib, R., Lefebvre, M., Ribeiro, J., Rousselle, J., & Trung, H. T. (2000). Application of diffusion processes to runoff estimation. Journal of Hydrologic Engineering, 5(1), 1-7. Lien externe

Labib, R. (2000). Processus de diffusion : outils de modélisation, de prévision et de contrôle [Thèse de doctorat, École Polytechnique de Montréal]. Disponible

Labib, R. (juillet 1999). New single neuron structure for solving nonlinear problems [Communication écrite]. International Joint Conference on Neural Networks (IJCNN 1999), Washington, DC, USA. Lien externe

Lefebvre, M., & Labib, R. (juin 1996). Risk sensitive optimal control of wear processes [Communication écrite]. AMS/SIAM Seminar on Mathematics of Stochastic Manufacturing Systems, Williamsburg, VA, USA. Non disponible

Lefebvre, M., & Labib, R. (juillet 1997). Risk sensitive optimal control of wear processes: the vector case [Communication écrite]. 18th IFIP TC7 Conference on Systems Modelling and Optimization, Boca Raton, FL, USA. Lien externe

Lefebvre, M., & Labib, R. (1997). Temps d'atteinte de cercles pour des processus de Bessel bidimensionnels. Annales des sciences mathématiques du Québec, 21(2), 123-131. Lien externe

Lefebvre, M., & Labib, R. (1996). Hitting lines and circles with diffusion processes. Australian Journal of Statistics, 38(2), 213-222. Lien externe

Labib, R., Lefebvre, M., Ribeiro, J., & Rousselle, J. (1996). Modèles utilisant les processus de diffusion comme outils de prévision. (Rapport technique). Non disponible

Lefebvre, M., & Labib, R. (août 1996). Modelling and controlling the flow of a river [Présentation]. Dans 16th Nordic Conference on Mathematical Statistics, Lahti, Finlande. Non disponible

Labib, R. (1995). Problèmes de premier passage pour des processus de Bessel [Mémoire de maîtrise, École Polytechnique de Montréal]. Non disponible

P

Pasquier, P., Zarrella, A., & Labib, R. (2018). Application of artificial neural networks to near-instant construction of short-term g-functions. Applied Thermal Engineering, 143, 910-921. Lien externe

R

Ratle, F., Lecarpentier, B., Labib, R., & Trochu, F. (septembre 2004). Multi-objective optimization of a composite material spring design using an evolutionary algorithm [Communication écrite]. 8th International Conference on Parallel Problem Solving from Nature (PPSN 2004), Birmingham, UK. Lien externe

S

Sharif Azadeh, S., Labib, R., & Savard, G. (2013). Railway demand forecasting in revenue management using neural networks. International Journal of Revenue Management, 7(1), 18-36. Lien externe

Z

Zagre, G. E., Gamache, M., Labib, R., & Shlenchak, V. (2023). Machine learning algorithms for real-time coal recognition using monitor-while-drilling data. International Journal of Mining, Reclamation and Environment, 26 pages. Lien externe

Liste produite: Fri Dec 20 03:42:24 2024 EST.