Continuous and timed Petri nets for the macroscopic and microscopic traffic flow modelling C Tolba, D Lefebvre, P Thomas, A El Moudni Simulation Modelling Practice and Theory 13 (5), 407-436, 2005 | 140 | 2005 |
A new multilayer perceptron pruning algorithm for classification and regression applications P Thomas, MC Suhner Neural Processing Letters 42, 437-458, 2015 | 63 | 2015 |
Continuous Petri nets models for the analysis of traffic urban networks C Tolba, D Lefebvre, P Thomas, A El Moudni 2001 IEEE International Conference on Systems, Man and Cybernetics. e …, 2001 | 59 | 2001 |
Performances evaluation of the traffic control in a single crossroad by Petri nets C Tolba, P Thomas, A ElMoudni, D Lefebvre EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory …, 2003 | 48 | 2003 |
Neural modeling of an induction furnace using robust learning criteria P Thomas, G Bloch, F Sirou, V Eustache Integrated Computer-Aided Engineering 6 (1), 15-26, 1999 | 43 | 1999 |
A neural network approach for freeway traffic flow prediction N Messai, P Thomas, D Lefebvre, A El Moudni Proceedings of the international conference on control applications 2, 984-989, 2002 | 41 | 2002 |
Using a classifier ensemble for proactive quality monitoring and control: The impact of the choice of classifiers types, selection criterion, and fusion process P Thomas, HB El Haouzi, MC Suhner, A Thomas, E Zimmermann, ... Computers in Industry 99, 193-204, 2018 | 33 | 2018 |
Multilayer perceptron for simulation models reduction: Application to a sawmill workshop P Thomas, A Thomas Engineering Applications of Artificial Intelligence 24 (4), 646-657, 2011 | 28 | 2011 |
Semi-supervised learning edited by O. Chapelle, B. Schölkopf and A. Zien P Thomas IEEE Transactions on Neural Networks 20 (3), 542, 2009 | 26 | 2009 |
Initialization of one hidden layer feedforward neural networks for non-linear system identification P Thomas, G Bloch 15th IMACS World Congress on Scientific Computation, Modelling and Applied …, 1997 | 26 | 1997 |
Neural networks for local monitoring of traffic magnetic sensors N Messai, P Thomas, D Lefebvre, A El Moudni Control Engineering Practice 13 (1), 67-80, 2005 | 23 | 2005 |
From batch to recursive outlier-robust identification of non-linear dynamic systems with neural networks P Thomas, G Bloch Proceedings of International Conference on Neural Networks (ICNN'96) 1, 178-183, 1996 | 22 | 1996 |
A neural network for the reduction of a product-driven system emulation model P Thomas, A Thomas, MC Suhner Production Planning & Control 22 (8), 767-781, 2011 | 19 | 2011 |
Optimal neural networks architectures for the flow–density relationships of traffic models N Messai, P Thomas, D Lefebvre, A El Moudni Mathematics and computers in simulation 60 (3-5), 401-409, 2002 | 18 | 2002 |
Implantation of an on-line quality process monitoring M Noyel, P Thomas, P Charpentier, A Thomas, T Brault Proceedings of 2013 International Conference on Industrial Engineering and …, 2013 | 17 | 2013 |
Improving production process performance thanks to neuronal analysis M Noyel, P Thomas, P Charpentier, A Thomas, B Beaupretre IFAC Proceedings Volumes 46 (7), 432-437, 2013 | 17 | 2013 |
Fault detection and isolation in non-linear systems by using oversized neural networks P Thomas, D Lefebvre Mathematics and computers in simulation 60 (3-5), 181-192, 2002 | 15 | 2002 |
Accommodation to outliers in identification of non linear SISO systems with neural networks G Bloch, P Thomas, D Theilliol Neurocomputing 14 (1), 85-99, 1997 | 15 | 1997 |
An iterative closest point method for measuring the level of similarity of 3D log scans in wood industry C Selma, H Bril El Haouzi, P Thomas, J Gaudreault, M Morin Service Orientation in Holonic and Multi-Agent Manufacturing: Proceedings of …, 2018 | 14 | 2018 |
Reconfiguration process for neuronal classification models: Application to a quality monitoring problem M Noyel, P Thomas, A Thomas, P Charpentier Computers in Industry 83, 78-91, 2016 | 14 | 2016 |