A new RBF neural network for prediction in industrial control AJ Telmoudi, H Tlijani, L Nabli, M Ali, R M'hiri International Journal of Information Technology & Decision Making 11 (04 …, 2012 | 23 | 2012 |
Computing intervals constrainted petri nets: A tobacco manufacturing application H Dhouibi, SC Dutilleul, E Craye, L Nabli IMACS conference, Paris, 440-446, 2005 | 19 | 2005 |
Surveillance préventive conditionnelle prévisionnelle indirecte d'une unité de filature textile: approche par la qualité L Nabli Lille 1, 2000 | 18 | 2000 |
Using Interval Constrained Petri Nets for reactive control design: a tobacco manufacturing application H Dhouibi, SD Collart, L Nabli, E Craye Journal for Manufacturing Science and Production 9 (3-4), 217-228, 2008 | 13 | 2008 |
Nonlinear system monitoring using multiscaled principal components analysis based on neural network HC Jebril, K Ouni, L Nabli International Journal of Modelling, Identification and Control 27 (1), 68-73, 2017 | 11 | 2017 |
The indirect supervision of a system of production by the principal components analysis and the average dynamics of the metrics L Nabli, K Ouni International Review of Automatic Control (IREACO) 1 (4), 2008 | 11 | 2008 |
The use of redundancy to evaluate the manufacturing system total robustness: A quality approach AJ Telmoudi, A Bourjault, L Nabli 2008 3rd International Symposium on Communications, Control and Signal …, 2008 | 11 | 2008 |
Modeling and analysis of a robust control of manufacturing systems: flow-quality approach L Nabli, AJ Telmoudi, R M’hiri International Journal of Computer, Information, and Systems Science, and …, 2008 | 11 | 2008 |
Segmenting and supervising an ECG signal by combining the CWT & PCA H Chaouch, K Ouni, L Nabli International Journal of Computer Science Issues (IJCSI) 9 (2), 433, 2012 | 10 | 2012 |
Modeling of Robustness Margins of the Control of a Predictive Control-Supervisory Architecture. AJ Telmoudi, L Nabli, R M'hiri J. Univers. Comput. Sci. 15 (17), 3231-3245, 2009 | 10 | 2009 |
Intelligent supervision approach based on multilayer neural PCA and nonlinear gain scheduling H Chaouch, S Charfedine, K Ouni, H Jerbi, L Nabli Neural Computing and Applications 31, 1153-1163, 2019 | 9 | 2019 |
New methods of Laguerre pole optimization for the ARX model expansion on Laguerre bases T Najeh, A Mbarek, K Bouzrara, L Nabli, H Messaoud ISA transactions 70, 93-103, 2017 | 9 | 2017 |
Approche Multi agents pour la surveillance indirecte d'un système de production par l'analyse en composantes principales L Nabli, K Ouni, HH Salem La Conférence Internationale Francophone d'Automatique CIFA, 128-136, 2008 | 9* | 2008 |
A petri nets based approach for the optimisation of surveillance patrols M Gam, D Lefebvre, L Nabli, AJ Telmoudi International Journal of Sensor Networks 36 (4), 181-193, 2021 | 8 | 2021 |
Configuration of surveillance patrols with Petri nets for safety issues GAM Marwa, D Lefebvre, AJ Telmoudi, L Nabli 2020 7th International Conference on Control, Decision and Information …, 2020 | 8 | 2020 |
Reconfigurable manufacturing system: Overview and proposition of new approach C Bettaieb, AJ Telmoudi, A Sava, L Nabli 2017 International Conference on Control, Automation and Diagnosis (ICCAD …, 2017 | 8 | 2017 |
Using interval constrained petri nets for regulation of quality: The case of weight in tobacco factory L Nabli, H Dhouibi International Journal of Intelligent Control and Systems, IJICS 13 (3), 178-188, 2008 | 8 | 2008 |
Minimum initial marking estimation of labeled petri nets based on GRASP inspired method (GMIM) A Abdellatif, A Jabeur Telmoudi, P Bonhomme, L Nabli Cybernetics and Systems 51 (4), 467-484, 2020 | 7 | 2020 |
Genetic-based approach for minimum initial marking estimation in labeled Petri nets H Kmimech, AJ Telmoudi, L Sliman, L Nabli IEEE Access 8, 22854-22861, 2020 | 7 | 2020 |
Méthode de surveillance indirecte d’un système de production par l’analyse en composantes principales L Nabli, K Ouni, H Messaoud La 5ème conférence internationale JTEA 2008, Journées Tunisiennes de l …, 2008 | 7 | 2008 |