A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots HA Hagras IEEE Transactions on Fuzzy systems 12 (4), 524-539, 2004 | 1219 | 2004 |
Type-2 FLCs: A new generation of fuzzy controllers H Hagras IEEE Computational Intelligence Magazine 2 (1), 30-43, 2007 | 580 | 2007 |
A historical account of types of fuzzy sets and their relationships H Bustince, E Barrenechea, M Pagola, J Fernandez, Z Xu, B Bedregal, ... IEEE Transactions on Fuzzy Systems 24 (1), 179-194, 2015 | 499 | 2015 |
Toward general type-2 fuzzy logic systems based on zSlices C Wagner, H Hagras IEEE transactions on fuzzy systems 18 (4), 637-660, 2010 | 452 | 2010 |
Creating an ambient-intelligence environment using embedded agents H Hagras, V Callaghan, M Colley, G Clarke, A Pounds-Cornish, H Duman IEEE Intelligent Systems 19 (6), 12-20, 2004 | 442 | 2004 |
Toward human-understandable, explainable AI H Hagras Computer 51 (9), 28-36, 2018 | 428 | 2018 |
A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments F Doctor, H Hagras, V Callaghan IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2004 | 406 | 2004 |
A survey of artificial intelligence techniques employed for adaptive educational systems within e-learning platforms K Colchester, H Hagras, D Alghazzawi, G Aldabbagh Journal of Artificial Intelligence and Soft Computing Research 7 (1), 47-64, 2017 | 381 | 2017 |
Introduction to type-2 fuzzy logic control: theory and applications J Mendel, H Hagras, WW Tan, WW Melek, H Ying John Wiley & Sons, 2014 | 355 | 2014 |
Ambient intelligence: A new multidisciplinary paradigm P Remagnino, GL Foresti IEEE Transactions on systems, man, and cybernetics-Part A: Systems and …, 2004 | 338 | 2004 |
A type-2 fuzzy ontology and its application to personal diabetic-diet recommendation CS Lee, MH Wang, H Hagras IEEE Transactions on Fuzzy Systems 18 (2), 374-395, 2010 | 285 | 2010 |
What computing with words means to me [discussion forum] JM Mendel, LA Zadeh, E Trillas, R Yager, J Lawry, H Hagras, ... IEEE computational intelligence magazine 5 (1), 20-26, 2010 | 271 | 2010 |
A compact evolutionary interval-valued fuzzy rule-based classification system for the modeling and prediction of real-world financial applications with imbalanced data JA Sanz, D Bernardo, F Herrera, H Bustince, H Hagras IEEE Transactions on Fuzzy Systems 23 (4), 973-990, 2014 | 203 | 2014 |
Interval type-2 fuzzy sets are generalization of interval-valued fuzzy sets: Toward a wider view on their relationship HB Sola, J Fernandez, H Hagras, F Herrera, M Pagola, E Barrenechea IEEE Transactions on Fuzzy Systems 23 (5), 1876-1882, 2014 | 198 | 2014 |
An incremental adaptive life long learning approach for type-2 fuzzy embedded agents in ambient intelligent environments H Hagras, F Doctor, V Callaghan, A Lopez IEEE Transactions on Fuzzy Systems 15 (1), 41-55, 2007 | 177 | 2007 |
Interval type-2 fuzzy logic congestion control for video streaming across IP networks EA Jammeh, M Fleury, C Wagner, H Hagras, M Ghanbari IEEE Transactions on Fuzzy Systems 17 (5), 1123-1142, 2009 | 175 | 2009 |
Towards the wide spread use of type-2 fuzzy logic systems in real world applications H Hagras, C Wagner IEEE computational intelligence magazine 7 (3), 14-24, 2012 | 165 | 2012 |
Evolving spiking neural network controllers for autonomous robots H Hagras, A Pounds-Cornish, M Colley, V Callaghan, G Clarke IEEE International Conference on Robotics and Automation, 2004. Proceedings …, 2004 | 138 | 2004 |
A hierarchical fuzzy–genetic multi-agent architecture for intelligent buildings online learning, adaptation and control H Hagras, V Callaghan, M Colley, G Clarke Information Sciences 150 (1-2), 33-57, 2003 | 137 | 2003 |
A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments F Doctor, H Hagras, V Callaghan Information Sciences 171 (4), 309-334, 2005 | 123 | 2005 |