| Discussion and review on evolving data streams and concept drift adapting I Khamassi, M Sayed-Mouchaweh, M Hammami, K Ghédira Evolving systems 9, 1-23, 2018 | 251 | 2018 |
| An overview on fault diagnosis and nature-inspired optimal control of industrial process applications RE Precup, P Angelov, BSJ Costa, M Sayed-Mouchaweh Computers in Industry 74, 75-94, 2015 | 198 | 2015 |
| Learning in non-stationary environments: methods and applications M Sayed-Mouchaweh, E Lughofer Springer Science & Business Media, 2012 | 193 | 2012 |
| Predictive maintenance in dynamic systems: advanced methods, decision support tools and real-world applications E Lughofer, M Sayed-Mouchaweh Springer, 2019 | 116 | 2019 |
| Autonomous data stream clustering implementing split-and-merge concepts–towards a plug-and-play approach E Lughofer, M Sayed-Mouchaweh Information Sciences 304, 54-79, 2015 | 116 | 2015 |
| Incremental learning in fuzzy pattern matching MS Mouchaweh, A Devillez, GV Lecolier, P Billaudel Fuzzy Sets and Systems 132 (1), 49-62, 2002 | 64 | 2002 |
| Active learning for classifying data streams with unknown number of classes S Mohamad, M Sayed-Mouchaweh, A Bouchachia Neural Networks 98, 1-15, 2018 | 51 | 2018 |
| Hybrid dynamic classifier for drift-like fault diagnosis in a class of hybrid dynamic systems: Application to wind turbine converters H Toubakh, M Sayed-Mouchaweh Neurocomputing 171, 1496-1516, 2016 | 49 | 2016 |
| A bi-criteria active learning algorithm for dynamic data streams S Mohamad, A Bouchachia, M Sayed-Mouchaweh IEEE transactions on neural networks and learning systems 29 (1), 74-86, 2016 | 47 | 2016 |
| Learning in dynamic environments M Sayed-Mouchaweh, M Sayed-Mouchaweh Learning from Data Streams in Dynamic Environments, 11-32, 2016 | 47 | 2016 |
| Self-adaptive windowing approach for handling complex concept drift I Khamassi, M Sayed-Mouchaweh, M Hammami, K Ghédira Cognitive Computation 7, 772-790, 2015 | 47 | 2015 |
| Hybrid dynamic data-driven approach for drift-like fault detection in wind turbines H Toubakh, M Sayed-Mouchaweh Evolving Systems 6 (2), 115-129, 2015 | 36 | 2015 |
| Semi-supervised classification method for dynamic applications MS Mouchaweh Fuzzy Sets and Systems 161 (4), 544-563, 2010 | 34 | 2010 |
| Online active learning for human activity recognition from sensory data streams S Mohamad, M Sayed-Mouchaweh, A Bouchachia Neurocomputing 390, 341-358, 2020 | 33 | 2020 |
| Decentralized fault diagnosis approach without a global model for fault diagnosis of discrete event systems M Sayed-Mouchaweh, E Lughofer International Journal of Control 88 (11), 2228-2241, 2015 | 33 | 2015 |
| A semi-supervised dynamic version of fuzzy k-nearest neighbours to monitor evolving systems L Hartert, M Sayed Mouchaweh, P Billaudel Evolving Systems 1, 3-15, 2010 | 33 | 2010 |
| Variable probability-possibility transformation MS Mouchaweh, MS Bouguelid, P Billaudel, B RiERA 25th European Annual Conference on Human Decision-Making and Manual Control …, 2006 | 33 | 2006 |
| Decentralized diagnosis based on Boolean discrete event models: application on manufacturing systems M Sayed-Mouchaweh, A Philippot, V Carré-Ménétrier International journal of production research 46 (19), 5469-5490, 2008 | 30 | 2008 |
| Control of DC–DC converter and DC motor dynamics using differential flatness theory G Rigatos, P Siano, P Wira, M Sayed-Mouchaweh Intelligent Industrial Systems 2, 371-380, 2016 | 29 | 2016 |
| Dynamic supervised classification method for online monitoring in non-stationary environments L Hartert, M Sayed-Mouchaweh Neurocomputing 126, 118-131, 2014 | 26 | 2014 |
Edwin LughoferJohannes Kepler University Linzjku.at의 이메일 확인됨
