Type-2 fuzzy tool condition monitoring system based on acoustic emission in micromilling Q Ren, M Balazinski, L Baron, K Jemielniak, R Botez, S Achiche Information Sciences 255, 121-134, 2014 | 109 | 2014 |
Type-2 Takagi-Sugeno-Kang fuzzy logic modeling using subtractive clustering Q Ren, L Baron, M Balazinski NAFIPS 2006-2006 Annual Meeting of the North American Fuzzy Information …, 2006 | 85 | 2006 |
TSK fuzzy modeling for tool wear condition in turning processes: an experimental study Q Ren, M Balazinski, L Baron, K Jemielniak Engineering Applications of Artificial Intelligence 24 (2), 260-265, 2011 | 61 | 2011 |
Experimental and fuzzy modelling analysis on dynamic cutting force in micro milling Q Ren, M Balazinski, K Jemielniak, L Baron, S Achiche Soft Computing 17, 1687-1697, 2013 | 46 | 2013 |
Fuzzy identification of cutting acoustic emission with extended subtractive cluster analysis Q Ren, L Baron, M Balazinski Nonlinear Dynamics 67, 2599-2608, 2012 | 29 | 2012 |
Modelling flint acoustics for detection of submerged Stone Age sites JP Hermand, O Grøn, M Asch, Q Ren OCEANS'11 MTS/IEEE KONA, 1-9, 2011 | 29 | 2011 |
High-order interval type-2 Takagi-Sugeno-Kang fuzzy logic system and its application in acoustic emission signal modeling in turning process Q Ren, M Balazinski, L Baron The International Journal of Advanced Manufacturing Technology 63, 1057-1063, 2012 | 27 | 2012 |
Tool wear assessment based on type-2 fuzzy uncertainty estimation on acoustic emission Q Ren, L Baron, M Balazinski, R Botez, P Bigras Applied Soft Computing 31, 14-24, 2015 | 25 | 2015 |
Type-2 TSK fuzzy logic system and its type-1 counterpart Q Ren, M Balazinski, L Baron International Journal of Computer Applications 20 (6), 8-13, 2011 | 24 | 2011 |
Tool condition monitoring using the TSK fuzzy approach based on subtractive clustering method Q Ren, M Balazinski, L Baron, K Jemielniak New Frontiers in Applied Artificial Intelligence: 21st International …, 2008 | 23 | 2008 |
Application of type-2 fuzzy estimation on uncertainty in machining: an approach on acoustic emission during turning process Q Ren, L Baron, M Balazinski NAFIPS 2009-2009 Annual Meeting of the North American Fuzzy Information …, 2009 | 21 | 2009 |
A highly accurate model-free motion control system with a Mamdani fuzzy feedback controller Combined with a TSK fuzzy feed-forward controller Q Ren, P Bigras Journal of Intelligent & Robotic Systems 86, 367-379, 2017 | 20 | 2017 |
Uncertainty prediction for tool wear condition using type-2 TSK fuzzy approach Q Ren, M Balazinski, L Baron 2009 IEEE International Conference on Systems, Man and Cybernetics, 660-665, 2009 | 19 | 2009 |
High order type-2 TSK fuzzy logic system Q Ren, L Baron, M Balazinski NAFIPS 2008-2008 Annual Meeting of the North American Fuzzy Information …, 2008 | 17 | 2008 |
Modelling of dynamic micromilling cutting forces using type-2 fuzzy rule-based system Q Ren, L Baron, K Jemielniak, M Balazinski International Conference on Fuzzy Systems, 1-7, 2010 | 16 | 2010 |
Acoustic emission signal feature analysis using type-2 fuzzy logic system Q Ren, L Baron, M Balazinski, K Jemielniak 2010 Annual Meeting of the North American Fuzzy Information Processing …, 2010 | 14 | 2010 |
Type‐2 Fuzzy Modeling for Acoustic Emission Signal in Precision Manufacturing Q Ren, L Baron, M Balazinski Modelling and Simulation in Engineering 2011 (1), 696947, 2011 | 12 | 2011 |
Type-2 Takagi-Sugeno-Kang fuzzy logic system and uncertainty in machining Q Ren Ecole Polytechnique, Montreal (Canada), 2012 | 10 | 2012 |
Space-frequency distribution of the vector field of broad-band sound in shallow water Q Ren, JP Hermand, S Piao OCEANS 2010 MTS/IEEE SEATTLE, 1-9, 2010 | 8 | 2010 |
An enhanced adaptive neural fuzzy tool condition monitoring for turning process Q Ren, S Achiche, K Jemielniak, P Bigras 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1976-1982, 2016 | 7 | 2016 |