Professor Hani Hagras

Kiani, M., Andreu-Perez, J. and Hagras, H., (2023). A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence. IEEE Transactions on Artificial Intelligence. 4 (3), 573-586

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2023). A Heated Stack based Type-2 Fuzzy Multi-Objective Optimisation System for Telecommunications Capacity Planning. Knowledge-Based Systems. 260, 110134-110134

Upasane, SJ., Hagras, H., Anisi, MH., Savill, S., Taylor, I. and Manousakis, K., (2023). A Type-2 Fuzzy Based Explainable AI System for Predictive Maintenance within the Water Pumping Industry. IEEE Transactions on Artificial Intelligence. 5 (2), 490-504

Almaraash, M., Abdulrahim, M. and Hagras, H., (2023). A Life-Long Learning XAI Metaheuristic-based Type-2 Fuzzy System for Solar Radiation Modelling. IEEE Transactions on Fuzzy Systems. 32 (4), 2102-2115

Kiani, M., Andreu-Perez, J., Hagras, H., Papageorgiou, EI., Prasad, M. and Lin, C-T., (2022). Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics. IEEE Transactions on Cognitive and Developmental Systems. 14 (1), 50-63

Yosr, G., Baklouti, N., Hagras, H., Ben ayed, M. and Alimi, AM., (2022). Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval. IEEE Transactions on Fuzzy Systems. 30 (3), 805-817

Cherif, S., Baklouti, N., Hagras, H. and Alimi., AM., (2022). Novel Intuitionistic Based Interval Type-2 Fuzzy Similarity Measures with Application to Clustering. IEEE Transactions on Fuzzy Systems. 30 (5), 1260-1271

Leon-Garza, H., Hagras, H., Peña-Rios, A., Conway, A. and Owusu, G., (2022). A type-2 fuzzy system-based approach for image data fusion to create building information models. Information Fusion. 88, 115-125

Andreu-Perez, J., Hagras, H., Kiani, M., Rigato, S. and Filippetti, ML., (2022). Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives. IEEE Computational Intelligence Magazine. 17 (1), 16-33

Mai, DS., Ngo, LT., Trinh, LH. and Hagras, H., (2021). A hybrid interval type-2 semi-supervised possibilistic fuzzy c-means clustering and particle swarm optimization for satellite image analysis. Information Sciences. 548, 398-422

Boumhidi, J., Nfaoui, EH., Hagras, H. and Vellasco, M., (2021). Special issue on Recent Advances in Computational Intelligence and Cognitive Systems (RACICS). Cognitive Systems Research. 70, 63-63

Andreu-Perez, J., Emberson, LL., Kiani, M., Filippetti, ML., Hagras, H. and Rigato, S., (2021). Explainable Artificial Intelligence Based Analysis for Developmental Cognitive Neuroscience. Communications Biology. 4 (1), 1077-

Wolfe, JC., Mikheeva, LA., Hagras, H. and Zabet, NR., (2021). An explainable artificial intelligence approach for decoding the enhancer histone modifications code and identification of novel enhancers in Drosophila. Genome Biology. 22 (1), 308-

Mendel, JM., Chimatapu, R. and Hagras, H., (2020). Comparing the Performance Potentials of Singleton and Non-singleton Type-1 and Interval Type-2 Fuzzy Systems in Terms of Sculpting the State Space. IEEE Transactions on Fuzzy Systems. 28 (4), 783-794

Veryard, L., Hagras, H., Starkey, A., Conway, A. and Owusu, G., (2020). NNIR: N-Non-Intersecting-Routing Algorithm for Multi-Path Resilient Routing in Telecommunications Applications. International Journal of Computational Intelligence Systems. 13 (1), 352-352

Jarraya, Y., Bouaziz, S., Hagras, H. and Alimi, AM., (2019). A Multi-Agent Architecture for the Design of Hierarchical Interval Type-2 Beta Fuzzy System. IEEE Transactions on Fuzzy Systems. 27 (6), 1174-1188

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2019). iPatch: A Many-Objective Type-2 Fuzzy Logic System for Field Workforce Optimisation. IEEE Transactions on Fuzzy Systems. 27 (3), 502-514

Liu, Y., Rodriguez, RM., Hagras, H., Liu, H., Qin, K. and Martinez, L., (2019). Type-2 Fuzzy Envelope of Hesitant Fuzzy Linguistic Term Set: A New Representation Model of Comparative Linguistic Expression. IEEE Transactions on Fuzzy Systems. 27 (12), 2312-2326

Ruiz-Garcia, G., Hagras, H., Pomares, H. and Ruiz, IR., (2019). Toward a Fuzzy Logic System Based on General Forms of Interval Type-2 Fuzzy Sets. IEEE Transactions on Fuzzy Systems. 27 (12), 2381-2395

(2019). Erratum. Computer. 52 (1), 57-57

Andreu-Perez, J., Cao, F., Hagras, H. and Yang, G., (2018). A Self-Adaptive Online Brain Machine Interface of a Humanoid Robot through a General Type-2 Fuzzy Inference System. IEEE Transactions on Fuzzy Systems. 26 (1), 101-116

Pena Rios, AC., Hagras, H., Owusu, G. and Gardner, M., (2018). Furthering Service 4.0: Harnessing Intelligent Immersive Environments and Systems. IEEE Systems, Man, and Cybernetics Magazine. 4 (1), 20-31

Hagras, H. and Cosby, K., (2018). HOW GREAT WAS LOTFI ZADEH?: A FUZZY TRIBUTE TO AN INFLUENTIAL FIGURE IN COMPUTING. COMPUTER. 51 (1), 100-102

Hagras, H., (2018). Toward Human-Understandable, Explainable AI. Computer. 51 (9), 28-36

Starkey, AJ., Hagras, H., Shakya, S. and Owusu, G., (2018). A Genetic Algorithm Based System for Simultaneous Optimisation of Workforce Skills and Teams. KI - Künstliche Intelligenz. 32 (4), 245-260

Colchester, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms. Journal of Artificial Intelligence and Soft Computing Research. 7 (1), 47-64

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2017). A zSlices-based general type-2 fuzzy logic system for users-centric adaptive learning in large-scale e-learning platforms. Soft Computing. 21 (22), 6859-6880

Almohammadi, K., Hagras, H., Yao, B., Alzahrani, A., Alghazzawi, D. and Aldabbagh, G., (2017). A type-2 fuzzy logic recommendation system for adaptive teaching. Soft Computing. 21 (4), 965-979

Ruiz-García, G., Hagras, H., Rojas, I. and Pomares, H., (2017). Towards a framework for singleton general forms of interval type-2 fuzzy systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10147 LNAI, 3-26

Antonelli, M., Bernardo, D., Hagras, H. and Marcelloni, F., (2017). Multiobjective Evolutionary Optimization of Type-2 Fuzzy Rule-Based Systems for Financial Data Classification. IEEE Transactions on Fuzzy Systems. 25 (2), 249-264

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Khanesar, MA. and Hagras, H., (2017). Novel Levenberg–Marquardt based learning algorithm for unmanned aerial vehicles. Information Sciences. 417, 361-380

Nadeem, F., Alghazzawi, D., Mashat, A., Fakeeh, K., Almalaise, A. and Hagras, H., (2017). Modeling and predicting execution time of scientific workflows in the Grid using radial basis function neural network. Cluster Computing. 20 (3), 2805-2819

De Miguel, L., Santos, H., Sesma-Sara, M., Bedregal, B., Jurio, A., Bustince, H. and Hagras, H., (2017). Type-2 Fuzzy Entropy-Sets. IEEE Transactions on Fuzzy Systems. 25 (4), 993-1005

Acampora, G., Siciliano, B., Hagras, H. and Herrera, F., (2017). Conference Report on 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017) [Conference Reports]. IEEE Computational Intelligence Magazine. 12 (4), 6-8

Wei, S., Hagras, H. and Alghazzawi, D., (2016). A cloud computing based Big-Bang Big-Crunch fuzzy logic multi classifier system for Soccer video scenes classification. Memetic Computing. 8 (4), 307-323

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). A multi-objective genetic type-2 fuzzy logic based system for mobile field workforce area optimization. Information Sciences. 329, 390-411

Bilgin, A., Hagras, H., van Helvert, J. and Alghazzawi, D., (2016). A Linear General Type-2 Fuzzy Logic Based Computing With Words Approach for Realising an Ambient Intelligent Platform for Cooking Recipes Recommendation. IEEE Transactions on Fuzzy Systems. 24 (2), 306-329

Starkey, A., Hagras, H., Shakya, S., Owusu, G., Mohamed, A. and Alghazzawi, D., (2016). A cloud computing based many objective type-2 fuzzy logic system for mobile field workforce area optimization. Memetic Computing. 8 (4), 269-286

Bustince, H., Barrenechea, E., Pagola, M., Fernandez, J., Xu, Z., Bedregal, B., Montero, J., Hagras, H., Herrera, F. and De Baets, B., (2016). A Historical Account of Types of Fuzzy Sets and Their Relationships. IEEE Transactions on Fuzzy Systems. 24 (1), 179-194

Mendel, JM., Hagras, H., Bustince, H. and Herrera, F., (2016). Comments on: Interval Type-2 Fuzzy Sets are generalization of Interval-Valued Fuzzy Sets: Towards a Wider view on their relationship. IEEE Transactions on Fuzzy Systems. 24 (1), 249-250

Ruiz, G., Hagras, H., Pomares, H., Rojas, I. and Bustince, H., (2016). Join and Meet Operations for Type-2 Fuzzy Sets With Nonconvex Secondary Memberships. IEEE Transactions on Fuzzy Systems. 24 (4), 1000-1008

Acampora, G., Alghazzawi, D., Hagras, H. and Vitiello, A., (2016). An interval type-2 fuzzy logic based framework for reputation management in Peer-to-Peer e-commerce. Information Sciences. 333, 88-107

Almohammadi, K., Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2016). Users-Centric Adaptive Learning System Based on Interval Type-2 Fuzzy Logic for Massively Crowded E-Learning Platforms. Journal of Artificial Intelligence and Soft Computing Research. 6 (2), 81-101

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2016). A Big Bang–Big Crunch Type-2 Fuzzy Logic System for Machine-Vision-Based Event Detection and Summarization in Real-World Ambient-Assisted Living. IEEE Transactions on Fuzzy Systems. 24 (6), 1307-1319

Yao, B., Hagras, H., Alhaddad, MJ. and Alghazzawi, D., (2015). A fuzzy logic-based system for the automation of human behavior recognition using machine vision in intelligent environments. Soft Computing. 19 (2), 499-506

Alhaddad, MJ., Mohammed, A., Kamel, M. and Hagras, H., (2015). A genetic interval type-2 fuzzy logic-based approach for generating interpretable linguistic models for the brain P300 phenomena recorded via brain–computer interfaces. Soft Computing. 19 (4), 1019-1035

Bilgin, A., Hagras, H., Ghelli, A., Alghazzawi, D. and Aldabbagh, G., (2015). An Ambient Intelligent and Energy Efficient Food Preparation System Using Linear General Type-2 Fuzzy Logic Based Computing with Words Framework [Application Notes]. IEEE Computational Intelligence Magazine. 10 (4), 66-78

Hagras, H., Alghazzawi, D. and Aldabbagh, G., (2015). Employing Type-2 Fuzzy Logic Systems in the Efforts to Realize Ambient Intelligent Environments [Application Notes]. IEEE Computational Intelligence Magazine. 10 (1), 44-51

Ghelli, A., Hagras, H. and Aldabbagh, G., (2015). A Fuzzy Logic Based Retrofit System for Enabling Smart Energy Efficient Electric Cookers. IEEE Transactions on Fuzzy Systems. 23 (6), 1984-1997

Kumbasar, T. and Hagras, H., (2015). A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller. IEEE Transactions on Fuzzy Systems. 23 (4), 991-1013

Sola, HB., Fernandez, J., Hagras, H., Herrera, F., Pagola, M. and Barrenechea, E., (2015). Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Toward a Wider View on Their Relationship. IEEE Transactions on Fuzzy Systems. 23 (5), 1876-1882

Sanz, JA., Bernardo, D., Herrera, F., Bustince, H. and Hagras, H., (2015). A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data. IEEE Transactions on Fuzzy Systems. 23 (4), 973-990

Naim, S. and Hagras, H., (2014). A type 2-hesitation fuzzy logic based multi-criteria group decision making system for intelligent shared environments. Soft Computing. 18 (7), 1305-1319

Kumbasar, T. and Hagras, H., (2014). Big Bang–Big Crunch optimization based interval type-2 fuzzy PID cascade controller design strategy. Information Sciences. 282, 277-295

Bernardo, D., Hagras, H. and Tsang, E., (2013). A genetic type-2 fuzzy logic based system for the generation of summarised linguistic predictive models for financial applications. Soft Computing. 17 (12), 2185-2201

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2013). Towards a linear general type-2 fuzzy logic based approach for computing with words. Soft Computing. 17 (12), 2203-2222

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). A Fuzzy Logic-Based System for Indoor Localization Using WiFi in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 21 (4), 702-718

Mendel, JM., Hagras, H. and John, RI., (2013). Guest Editorial for the special issue on type-2 fuzzy sets and systems. IEEE Transactions on Fuzzy Systems. 21 (3), 397-398

Cara, AB., Wagner, C., Hagras, H., Pomares, H. and Rojas, I., (2013). Multiobjective Optimization and Comparison of Nonsingleton Type-1 and Singleton Interval Type-2 Fuzzy Logic Systems. IEEE Transactions on Fuzzy Systems. 21 (3), 459-476

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). The Tailored Fabric of Intelligent Environments. Studies in Computational Intelligence. 460, 321-344

Huang, H-D., Acampora, G., Loia, V., Lee, C-S., Hagras, H., Wang, M-H., Kao, H-Y. and Chang, J-G., (2013). Fuzzy Markup Language for Malware Behavioral Analysis. Studies in Fuzziness and Soft Computing. 296, 113-132

Wang, M-H., Lee, C-S., Hagras, H., Su, M-K., Tseng, Y-Y., Wang, H-M., Wang, Y-L. and Liu, C-H., (2013). Applying FML-Based Fuzzy Ontology to University Assessment. Studies in Fuzziness and Soft Computing. 296, 133-147

Wang, M-H., Lee, C-S., Chen, Z-W., Hagras, H., Kuo, S-E., Kuo, H-C. and Cheng, H-H., (2013). A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment. Studies in Fuzziness and Soft Computing. 296, 149-168

Lee, C-S., Wang, M-H., Su, M-K., Wu, M-H. and Hagras, H., (2013). A Type-2 FML-Based Meeting Scheduling Support System. Studies in Fuzziness and Soft Computing. 296, 169-187

Garcia-Valverde, T., Garcia-Sola, A., Hagras, H., Dooley, JA., Callaghan, V. and Botia, JA., (2013). A Fuzzy Logic-Based System for Indoor Localization Using WiFi in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 21 (4), 702-718

Naim, S. and Hagras, H., (2013). A Big-Bang Big-Crunch Optimized General Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making. Journal of Artificial Intelligence and Soft Computing Research. 3 (2), 117-132

Hagras, H. and Wagner, C., (2012). Towards the Wide Spread Use of Type-2 Fuzzy Logic Systems in Real World Applications. IEEE Computational Intelligence Magazine. 7 (3), 14-24

LEE, C-S., WANG, M-H., HAGRAS, H., CHEN, Z-W., LAN, S-T., HSU, C-Y., KUO, S-E., KUO, H-C. and CHENG, H-H., (2012). A NOVEL GENETIC FUZZY MARKUP LANGUAGE AND ITS APPLICATION TO HEALTHY DIET ASSESSMENT. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 20 (supp02), 247-278

Wagner, C., Goumopoulos, C. and Hagras, H., (2012). Emerging and adaptive fuzzy logic based behaviours in activity sphere centred ambient ecologies. Pervasive and Mobile Computing. 8 (4), 500-521

Lee, C-S., Wang, M-H., Chen, Y-J., Hagras, H., Wu, M-J. and Teytaud, O., (2012). Genetic fuzzy markup language for game of NoGo. Knowledge-Based Systems. 34, 64-80

Hagras, H., Wagner, C., Kameas, A., Goumopoulos, C., Meliones, A., Seremeti, L., Heinroth, T., Minker, W., Bellik, Y. and Pruvost, G., (2012). Symbiotic Ecologies in Next Generation Ambient Intelligent Environments.. Int. J. Next Gener. Comput.. 3

Hagras, H. and Wagner, C., (2012). Towards the Widespread Use of Type-2 Fuzzy Logic Systems in Real World Applications. IEEE Computational Intelligence Magazine. 7 (3), 14-24

Lee, C., Wang, M., Hagras, H., Chen, Z., Lan, S., Hsu, C., Kuo, S., Kuo, H. and Cheng, H., (2012). A novel genetic fuzzy markup language and its application to healthy diet assessment. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 20 (2), 247-278

Sahab, N. and Hagras, H., (2011). Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications. International Journal of Computers, Communications and Control. 5 (3), 503-529

Sahab, N. and Hagras, H., (2011). Adaptive Non-singleton Type-2 Fuzzy Logic Systems: A Way Forward for Handling Numerical Uncertainties in Real World Applications. International Journal of Computers Communications & Control. 6 (3), 503-503

Duman, H., Hagras, H. and Callaghan, V., (2010). A multi-society-based intelligent association discovery and selection for ambient intelligence environments. ACM Transactions on Autonomous and Adaptive Systems. 5 (2), 1-34

Rivera-illingworth, F., Callaghan, V. and Hagras, H., (2010). Detection Of Normal and Novel Behaviours In Ubiquitous Domestic Environments. The Computer Journal. 53 (2), 142-151

Callaghan, V. and Hagras, H., (2010). Preface. Journal of Ambient Intelligence and Smart Environments. 2 (3), 207-209

Wagner, C. and Hagras, H., (2010). Toward General Type-2 Fuzzy Logic Systems Based on zSlices. IEEE Transactions on Fuzzy Systems. 18 (4), 637-660

Lee, Wang and Hagras, (2010). A Type-2 Fuzzy Ontology and its Application to Personal Diabetic Diet Recommendation. IEEE Transactions on Fuzzy Systems. 18 (2), 374-395

Lee, C-S., Wang, M-H., Acampora, G., Hsu, C-Y. and Hagras, H., (2010). Diet assessment based on type-2 fuzzy ontology and fuzzy markup language. International Journal of Intelligent Systems. 25 (12), 1187-1216

Mendel, J., Zadeh, L., Trillas, E., Yager, R., Lawry, J., Hagras, H. and Guadarrama, S., (2010). What Computing with Words Means to Me [Discussion Forum. IEEE Computational Intelligence Magazine. 5 (1), 20-26

Lee, C., Wang, M., Acampora, G., Hsu, C. and Hagras, H., (2010). Type-2 Fuzzy Markup Language Based Ontology and Its Application to Diet Assessment. The International Journal of Intelligent Systems. 25 (12), 1187-1216

Tawil, E. and Hagras, H., (2009). An Adaptive Genetic-Based Incremental Architecture for the On-Line Coordination of Embedded Agents. Cognitive Computation. 1 (4), 300-326

Jammeh, EA., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2009). Interval Type-2 Fuzzy Logic Congestion Control for Video Streaming Across IP Networks. IEEE Transactions on Fuzzy Systems. 17 (5), 1123-1142

Cook, DJ., Hagras, H., Callaghan, V. and Helal, A., (2009). Making our environments intelligent. Pervasive and Mobile Computing. 5 (5), 556-557

Hagras, H., Callaghan, V., Cook, D. and Helal, A., (2009). The Fourth International Conference on Intelligent Environments (IE 08): A Report. AI Magazine. 30 (1), 124-125

Hagras, H., Ramadan, R., Wanas, N., Nawito, M., Mohamed, N., Aly, S. and Moustafa, M., (2009). Egypt Chapter Report [Family Corner]. IEEE Computational Intelligence Magazine. 4 (4), 13-16

Hagras, H. and Wagner, C., (2009). Introduction to Interval Type-2 Fuzzy Logic Controllers - Towards Better Uncertainty Handling in Real World Applications. The IEEE Systems, Man and Cybernetics eNewsletter (27)

Duman, H., Hagras, H. and Callaghan, V., (2008). Intelligent Association Exploration and Exploitation of Fuzzy Agents in Ambient Intelligent Environments. Journal of Uncertain Systems. 2 (2), 133-143

Hagras, H., (2008). Employing computational intelligence to generate more intelligent and energy efficient living spaces. International Journal of Automation and Computing. 5 (1), 1-9

Hagras, H., (2007). Embedding Computational Intelligence in Pervasive Spaces. IEEE Pervasive Computing. 6 (3), 85-89

Hagras, H., (2007). Type-2 FLCs: A New Generation of Fuzzy Controllers. IEEE Computational Intelligence Magazine. 2 (1), 30-43

Hagras, H., Doctor, F., Callaghan, V. and Lopez, A., (2007). An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments. IEEE Transactions on Fuzzy Systems. 15 (1), 41-55

Duman, H., Hagras, H. and Callaghan, V., (2007). Intelligent association selection of embedded agents in intelligent inhabited environments. Pervasive and Mobile Computing. 3 (2), 117-157

Hagras, H., (2006). Comments on "Dynamical optimal training for interval type-2 fuzzy neural network (THNN)". IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS. 36 (5), 1206-1209

Hagras, H., (2006). Comments on "Dynamical Optimal Training for Interval Type-2 Fuzzy Neural Network (T2FNN). IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 36 (5), 1206-1209

Doctor, F., Hagras, H. and Callaghan, V., (2005). A Fuzzy Embedded Agent-Based Approach for Realizing Ambient Intelligence in Intelligent Inhabited Environments. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 35 (1), 55-65

DOCTOR, F., HAGRAS, H. and CALLAGHAN, V., (2005). A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments. Information Sciences. 171 (4), 309-334

HAGRAS, H., CALLAGHAN, V. and COLLEY, M., (2005). Intelligent embedded agents. Information Sciences. 171 (4), 289-292

Callaghan, V., Clarke, G., Colley, M., Hagras, H., Chin, JSY. and Doctor, F., (2004). Inhabited Intelligent Environments. BT Technology Journal. 22 (3), 233-247

Hagras, H., Callaghan, V., Colley, M., Clarke, G., Pounds-Cornish, A. and Duman, H., (2004). Creating an Ambient-Intelligence Environment Using Embedded Agents. IEEE Intelligent Systems. 19 (06), 12-20

Hagras, H., Callaghan, V. and Colley, M., (2004). Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy–Genetic system. Fuzzy Sets and Systems. 141 (1), 107-160

Hagras, HA., (2004). A Hierarchical Type-2 Fuzzy Logic Control Architecture for Autonomous Mobile Robots. IEEE Transactions on Fuzzy Systems. 12 (4), 524-539

Attallah, A., (2004). Utility of a novel HCV-NS4 antigen detection immunoassay for monitoring treatment of HCV-infected individuals with pegylated interferon α-2a. Hepatology Research. 28 (2), 68-72

Schlaf, M., Hagras, H. and Sands, D., (2003). Optimization strategies for parametric analysis of thin-film reflectivity spectra. IEEE Transactions on Instrumentation and Measurement. 52 (5), 1635-1639

Hagras, H. and Sobh, T., (2002). Intelligent learning and control of autonomous robotic agents operating in unstructured environments. Information Sciences. 145 (1-2), 1-12

Hagras, H., Colley, M., Callaghan, V. and Carr-West, M., (2002). Online learning and adaptation of autonomous mobile robots for sustainable agriculture. Autonomous Robots. 13 (1), 37-52

Hagras, H., Callaghan, V. and Collry, M., (2001). Outdoor mobile robot learning and adaptation. IEEE Robotics & Automation Magazine. 8 (3), 53-69

Hagras, H., (2001). Computational intelligence techniques applied to cooperative multi-robotics systems. International Journal of Robotics and Automation. 16 (4)

Hagras, H., Callaghan, V. and Colley, M., (1999). An embedded‐agent technique for industrial control environments where process modelling is difficult. Assembly Automation. 19 (4), 323-331

Kumbasar, T. and Hagras, H., (2015). Interval Type-2 Fuzzy PID Controllers. In: Springer Handbook of Computational Intelligence. Editors: . Springer Berlin Heidelberg. 285- 294. 9783662435045

Kumbasar, T. and Hagras, H., (2015). Interval type-2 fuzzy pid controllers. In: Springer Handbook of Computational Intelligence. 285- 294

Naim, S. and Hagras, H., (2015). A Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making. In: Studies in Big Data. Springer International Publishing. 123- 164. 9783319168289

Huang, H-D., Acampora, G., Loia, V., Lee, C-S., Hagras, H., Wang, M-H., Kao, H-Y. and Chang, J-G., (2013). Fuzzy Markup Language for Malware Behavioral Analysis.. In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 113- 132. 978-3-642-35487-8

Dooley, J., Hagras, H., Callaghan, V. and Henson, M., (2013). The Tailored Fabric of Intelligent Environments.. In: Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence. Editors: Bessis, N., Xhafa, F., Varvarigou, D., Hill, R. and Li, M., . Springer. 321- 344. 978-3-642-34951-5

Lee, C-S., Wang, M-H., Su, M-K., Wu, M-H. and Hagras, H., (2013). A Type-2 FML-Based Meeting Scheduling Support System.. In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 169- 187. 978-3-642-35487-8

Wang, M-H., Lee, C-S., Chen, Z-W., Hagras, H., Kuo, S-E., Kuo, H-C. and Cheng, H-H., (2013). A Type-2 FML-Based Fuzzy Ontology for Dietary Assessment.. In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 149- 168. 978-3-642-35487-8

Wang, M-H., Lee, C-S., Hagras, H., Su, M-K., Tseng, Y-Y., Wang, H-M., Wang, Y-L. and Liu, C-H., (2013). Applying FML-Based Fuzzy Ontology to University Assessment.. In: On the Power of Fuzzy Markup Language. Editors: Acampora, G., Loia, V., Lee, C-S. and Wang, M-H., . Springer. 133- 147. 978-3-642-35487-8

Shakya, S., Kassem, S., Mohamed, A., Hagras, H. and Owusu, G., (2013). Enhancing Field Service Operations via Fuzzy Automation of Tactical Supply Plan. In: Transforming Field and Service Operations. Editors: . Springer Berlin Heidelberg. 101- 114. 9783642449697

Wagner, C. and Hagras, H., (2013). ZSlices based general type-2 fuzzy sets and systems. In: Advances in Type-2 Fuzzy Sets and Systems. Editors: Sadeghian, A., Mendel, JM. and Tahayori, H., . Springer. 65- 80. 9781461466659

Hagras, H. and Wagner, C., (2011). Artefact Adaptation in Ambient Intelligent Environments. In: Next Generation Intelligent Environments: Ambient Adaptive Systems. Editors: Minker, W. and Heinroth, T., . Springer. 127- 151. 9781461412984

Hagras, H., (2011). Towards Online Adaptive Ambient Intelligent Environments for Multiple Occupants. In: Adaptive and Intelligent Systems. Editors: Bouchachia, A., . Springer. creators- Hagras=3AHani=3A=3A. 9783642238567

Hagras, H., (2011). Introduction to Type-2 Fuzzy Logic Controllers. In: The Industrial Electronics Handbook - Five Volume Set

Kameas, A., Goumopoulos, C., Hagras, H., Callaghan, V., Heinroth, T. and Weber, M., (2009). An Architecture that Supports Task-Centered Adaptation. In: Advanced Intelligent Environments. Editors: Kameas, AD., Callaghan, V., Hagras, H. and Weber, M., . Springer. 41- 69. 9780387764849

Al-Jaljouli, R. and Abawajy, J., (2009). Agents Based e-Commerce and Securing Exchanged Information. In: Computer Communications and Networks. Editors: . Springer London. 383- 404. 9781848825987

Gulrez, T., Tognetti, A. and De Rossi, D., (2009). Sensorized Garment Augmented 3D Pervasive Virtual Reality System. In: Computer Communications and Networks. Editors: . Springer London. 97- 115. 9781848825987

Haghighi, PD., Gaber, MM., Krishnaswamy, S. and Zaslavsky, A., (2009). Situation-Aware Adaptive Processing (SAAP) of Data Streams. In: Computer Communications and Networks. Editors: . Springer London. 313- 338. 9781848825987

Peters, JF., Szturm, T., Borkowski, M., Lockery, D., Ramanna, S. and Shay, B., (2009). Wireless Adaptive Therapeutic TeleGaming in a Pervasive Computing Environment. In: Computer Communications and Networks. Editors: . Springer London. 3- 28. 9781848825987

Pinzón, C., De Paz, Y., Bajo, J., Abraham, A. and Corchado, JM., (2009). SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases. In: Computer Communications and Networks. Editors: . Springer London. 231- 258. 9781848825987

Peterson, N., Anusuya-Rangappa, L., Shirazi, BA., Song, W., Huang, R., Tran, D., Chien, S. and LaHusen, R., (2009). Volcano Monitoring: A Case Study in Pervasive Computing. In: Computer Communications and Networks. Editors: . Springer London. 201- 230. 9781848825987

Fleury, M., Jammeh, EA., Razavi, R. and Ghanbari, M., (2009). Resource-Aware Fuzzy Logic Control of Video Streaming over IP and Wireless Networks. In: Pervasive Computing: Innovations in Intelligent Multimedia and Applications. Editors: Hassanien, A., Abawajy, JH., Abraham, A. and Hagras, H., . Springer. 47- 75. 9781848825987

Duman, H., Hagras, H. and Callaghan, V., (2007). Adding Intelligence to Ubiquitous Computing Environments. In: Studies in Computational Intelligence. Editors: . Springer Berlin Heidelberg. 61- 102. 9783540731757

Hagras, H., (2006). Fuzzy Logic Based Control Mechanisms for Handling the Uncertainties Facing Mobile Robots in Changing Unstructured Environments. In: Advances in Industrial Control. Springer London. 175- 189. 9781846284687

Remagnino, P., Hagras, H., Monekosso, N. and Velastin, S., (2005). Ambient Intelligence. In: Ambient Intelligence. Springer New York. 1- 14. 9780387229904

Fumanal-Idocin, J., Bustince, H., Andreu-Perez, J. and Hagras, H., (2023). On the Stability of Fuzzy Classifiers to Noise Induction

Hagras, H., (2023). Towards True Explainable Artificial Intelligence for Real World Applications

Bhatia, A. and Hagras, H., (2022). A Time Series Based Explainable Interval Type-2 Fuzzy Logic System

Leon-Garza, H., Hagras, H., Pena-Rios, A., Bahceci, O. and Conway, A., (2022). A Hand-Gesture Recognition Based Interpretable Type-2 Fuzzy Rule-based System for Extended Reality

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Fitz, S., (2021). A Type-2 Fuzzy Logic Based Explainable AI Approach for the Easy Calibration of AI models in IoT Environments

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2021). An Interval Type-2 Fuzzy-based System to Create Building Information Management Models from 2D Floor Plan Images

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2021). A Fuzzy Rule-based System using a Patch-based Approach for Semantic Segmentation in Floor Plans

Upasane, SJ., Hagras, H., Anisi, MH., Savill, S., Taylor, I. and Manousakis, K., (2021). A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Explainable Predictive Maintenance

Beasley, L., Hagras, H., Conway, A. and Owusu, G., (2021). A Type-2 Fuzzy Based Multi-Objective Optimisation for Strategic Network Planning in the Telecommunication Domain

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2021). A Type-2 Fuzzy Multi-Objective Multi-Chromosomal Optimisation for Capacity Planning within Telecommunication Networks

Chimatapu, R., Hagras, H., Kern, M. and Owusu, G., (2021). Enhanced Deep Type-2 Fuzzy Logic System For Global Interpretability

Bhatia, A. and Hagras, H., (2021). Identifying and Rectifying Rational Gaps in Fuzzy Rule Based Systems for Regression Problems

(2021). [Front matter]

Chimatapu, R., Hagras, H., Kern, M. and Owusu, G., (2020). Hybrid Deep Learning Type-2 Fuzzy Logic Systems For Explainable AI

Kiani, M., Andreu-Perez, J., Hagras, H., Filippetti, ML. and Rigato, S., (2020). A Type-2 Fuzzy Logic Based Explainable Artificial Intelligence System for Developmental Neuroscience

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Data, SF., (2020). Privacy-Preserving Gesture Recognition with Explainable Type-2 Fuzzy Logic Based Systems

Leon-Garza, H., Hagras, H., Pena-Rios, A., Conway, A. and Owusu, G., (2020). A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Explainable Semantic Segmentation of Trees in Satellite Images using HSV Color Space

Adams, J. and Hagras, H., (2020). A Type-2 Fuzzy Logic Approach to Explainable AI for regulatory compliance, fair customer outcomes and market stability in the Global Financial Sector

Leon-Garza, H., Hagras, H., Pena-Rios, A., Owusu, G. and Conway, A., (2020). A Fuzzy Logic Based System for Cloud-based Building Information Modelling Rendering Optimization in Augmented Reality

Veryard, L., Hagras, H., Conway, A. and Owusu, G., (2020). A Type-2 Fuzzy Genetic Approach to Uncertain & Dynamic Resilient Routing within Telecommunications Networks

Pena-Rios, A., Oplatek, T., Hagras, H., Conway, A. and Owusu, G., (2020). Work-in-Progress—Measuring Engagement in Virtual Reality for Talent Attraction Purposes

Al-Zeyadi, M., Andreu-Perez, J., Hagras, H., Royce, C., Smith, D., Rzonsowski, P. and Malik, A., (2020). Deep Learning Towards Intelligent Vehicle Fault Diagnosis

Pule, KE., Anisi, MH., Doctor, F. and Hagras, H., (2020). Multiple UAV based Spatio-Temporal Task Assignment using Fast Elitist Multi Objective Evolutionary Approaches

Steffens, A., Campello, A., Ravenscroft, J., Clark, A. and Hagras, H., (2019). Deep segmentation: Using deep convolutional networks for coral reef pixel-wise parsing

Veryard, L., Hagras, H., Starkey, A. and Owusu, G., (2019). A Fuzzy Genetic System for Resilient Routing in Uncertain & Dynamic Telecommunication Networks

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2019). Depicting Decision-Making: A Type-2 Fuzzy Logic Based Explainable Artificial Intelligence System for Goal-Driven Simulation in the Workforce Allocation Domain

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2019). Enabling Field Force Operational Sustainability: A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Goal-Driven Simulation

Kiani, M., Andreu-Perez, J., Hagras, H., Andreu, AR., Pinto, M., Andreu, J., Reddy, P. and Izzetoglu, K., (2019). Towards Gamers’ Experience Level Decoding with Optical Brain Imaging

(2019). ICDS 2019 Preface

Clift, LG., Lepley, J., Hagras, H. and Clark, A., (2018). Autonomous computational intelligence-based behaviour recognition in security and surveillance

Pena Rios, AC., Hagras, H., Owusu, G. and Gardner, M., (2018). A Type-2 Fuzzy Logic Based System for Augmented Reality Visualisation of Georeferenced Data

Kassa, DM. and Hagras, H., (2018). An Adaptive Segmentation Technique For the Ancient Ethiopian Ge’ez Language Digital Manuscripts

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Stacked Auto Encoder Based Hybrid Genetic Algorithm for Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). A Big-Bang Big-Crunch Type-2 Fuzzy Logic System for Generating Interpretable Models in Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Interval Type-2 Fuzzy Logic Based Stacked Autoencoder Deep Neural Network For Generating Explainable AI Models in Workforce Optimization

Chimatapu, R., Hagras, H., Starkey, A. and Owusu, G., (2018). Explainable AI and Fuzzy Logic Systems

Chimatapu, R., Hagras, H., Starkey, AJ. and Owusu, G., (2018). Enhancing Human Decision Making for Workforce Optimisation Using a Stacked Auto Encoder Based Hybrid Genetic Algorithm

Bhatia, A., Hagras, H. and Lepley, JJ., (2018). Machine Learning Approach to Extracting Emotions Information from Open Source Data for Relative Forecasting of Stock Prices

Ferreyra, E., Hagras, H., Kern, M. and Owusu, G., (2018). Improving Goal-Driven Simulation Performance Using Fuzzy Membership Correlation Analysis

Yusuf, HS. and Hagras, H., (2018). Towards Image Steganography Using Type-2 Fuzzy Logic and Edge Detection

Salih, A. and Hagras, H., (2018). Towards a Type-2 Fuzzy Logic Based System for Decision Support to Minimize Financial Default in Banking Sector

Saeed, SK. and Hagras, H., (2018). Adaptive Type-2 Fuzzy Logic Based System for Fraud Detection in Financial Applications

Mohammed, HA. and Hagras, H., (2018). Towards Developing Type 2 Fuzzy Logic Diet Recommendation System for Diabetes

Chekol, BE. and Hagras, H., (2018). Employing Machine Learning Techniques for the Malaria Epidemic Prediction in Ethiopia

Alhassan, MSE. and Hagras, H., (2018). Towards Congestion Control Approach Based on Weighted Random Early Detection and Type-2 Fuzzy Logic System

Yao, B., Hagras, H., Lepley, JJ., Peall, R. and Butler, M., (2017). An evolutionary optimization based interval type-2 fuzzy classification system for human behaviour recognition and summarisation

Yao, B., Hagras, H., Lepley, JJ., Peall, R. and Butler, M., (2017). An evolutionary optimization based interval type-2 fuzzy classification system for human behaviour recognition and summarisation

Pena-Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2017). A fuzzy logic based system for geolocated augmented reality field service support

Pena Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2017). A type-2 Fuzzy Logic based System for asset geolocation within augmented reality environments

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2017). Fuzzy dominance rules for real-world many objective optimization

Ferreyra, E., Hagras, H., Mohamed, A. and Owusu, G., (2017). A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain

Ruiz, G., Pomares, H., Rojas, I. and Hagras, H., (2017). The non-singleton fuzzification operation for general forms of interval type-2 fuzzy logic systems

Song, W. and Hagras, H., (2017). A type-2 fuzzy logic system for event detection in soccer videos

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). A comparison of particle swarm optimization and genetic algorithms for a multi-objective Type-2 fuzzy logic based system for the optimal allocation of mobile field engineers

Yao, B., Lepley, JJ., Peall, R., Butler, M. and Hagras, H., (2016). Recognition of complex human behaviours using 3D imaging for intelligent surveillance applications

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2016). A many-objective genetic type-2 fuzzy logic system for the optimal allocation of mobile field engineers

Pena-Rios, A., Hagras, H., Gardner, M. and Owusu, G., (2016). A Fuzzy Logic based system for Mixed Reality assistance of remote workforce

Song, W. and Hagras, H., (2016). A big-bang big-crunch fuzzy logic based system for sports video scene classification

Song, W. and Hagras, H., (2016). A big-bang big-crunch type-2 fuzzy logic based system for soccer video scene classification

Ruiz, G., Pomares, H., Rojas, I. and Hagras, H., (2016). Towards general forms of interval type-2 fuzzy logic systems

Bilgin, A., Hagras, H., Alghazzawi, D., Malibari, A. and Alhaddad, MJ., (2015). Employing an Enhanced Interval Approach to encode words into Linear General Type-2 fuzzy sets for Computing With Words applications

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2015). A genetic type-2 fuzzy logic based approach for the optimal allocation of mobile field engineers to their working areas

Almohammadi, K., Yao, B., Alzahrani, A., Hagras, H. and Alghazzawi, D., (2015). An interval type-2 fuzzy logic based system for improved instruction within intelligent e-learning platforms

Kumbasar, T. and Hagras, H., (2015). A Gradient Descent based online tuning Mechanism for PI Type Single input Interval Type-2 fuzzy logic controllers

Starkey, A., Hagras, H., Shakya, S. and Owusu, G., (2015). A Genetic Algorithm Based Approach for Workforce Upskilling.

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2014). A Type-2 Fuzzy Logic based system for linguistic summarization of video monitoring in indoor intelligent environments

Bilgin, A., Hagras, H., Upasane, S., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2014). An Adaptive Ambient Intelligent Platform for Recommending Recipes Using Computing with Words

Almohammadi, K., Yao, B. and Hagras, H., (2014). An interval type-2 fuzzy logic based system with user engagement feedback for customized knowledge delivery within intelligent E-learning platforms

Sakalli, A., Kumbasar, T., Yesil, E. and Hagras, H., (2014). Analysis of the performances of type-1, self-tuning type-1 and interval type-2 fuzzy PID controllers on the Magnetic Levitation system

Kumbasar, T., Ozturk, C., Yesil, E. and Hagras, H., (2014). Performance evaluation of interval type-2 and online rule weighing based Type-1 Fuzzy PID controllers on a pH process

Mohamed, A., Hagras, H., Shakya, S., Liret, A., Dorne, R. and Owusu, G., (2014). Hierarchical Type-2 Fuzzy Logic Based Real Time Dynamic Operational Planning System.

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2013). An experience based linear general type-2 fuzzy logic approach for Computing With Words

Bilgin, A., Hagras, H., Malibari, A., Alghazzawi, D. and Mohammed, J., (2013). A Computing with Words Framework for Ambient Intelligence

Bostanci, B., Hagras, H. and Dooley, J., (2013). A neuro fuzzy embedded agent approach towards the development of an intelligent refrigerator

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2013). A Type-2 fuzzy logic machine vision based approach for human behaviour recognition in intelligent environments

Bernardo, D., Hagras, H. and Tsang, E., (2013). A Genetic Type-2 fuzzy logic based system for financial applications modelling and prediction

Ghelli, A., Hagras, H. and Dooley, J., (2013). Towards realising an intelligent and energy efficient hob by employing a fuzzy logic based embedded agent approach

Almohammadi, K. and Hagras, H., (2013). An Interval Type-2 Fuzzy Logic Based System for Customised Knowledge Delivery within Pervasive E-Learning Platforms

Mohamed, A., Hagras, H., Liret, A., Shakya, S. and Owusu, G., (2013). A genetic interval type-2 fuzzy logic based approach for operational resource planning

Mohamed, A., Hagras, H., Shakya, S. and Owusu, G., (2013). A fuzzy-genetic tactical resource planner for workforce allocation

Almohammadi, K. and Hagras, H., (2013). An adaptive fuzzy logic based system for improved knowledge delivery within intelligent E-Learning platforms

Naim, S., Hagras, H. and Bilgin, A., (2013). Employing an interval type-2 fuzzy logic and hesitation index in a Multi Criteria Group Decision Making system for lighting level selection in an intelligent environment

Naim, S. and Hagras, H., (2013). A general type-2 fuzzy logic based approach for Multi-Criteria Group Decision Making

Torrejon, A., Callaghan, V. and Hagras, H., (2013). Selectable Directional Audio for Multiple Telepresence in Immersive Intelligent Environments

Torrejon, A., Callaghan, V. and Hagras, H., (2013). Improving Communication and Presence in Online Telepresence Systems

Yao, B., Hagras, H., Alghazzawi, D. and Alhaddad, MJ., (2013). A Big Bang-Big Crunch Optimization for a Type-2 Fuzzy Logic Based Human Behaviour Recognition System in Intelligent Environments

Kumbasar, T. and Hagras, H., (2013). A Type-2 Fuzzy Cascade Control Architecture for Mobile Robots

Kumbasar, T. and Hagras, H., (2013). A big bang-big crunch optimization based approach for interval type-2 fuzzy PID controller design

Nairm, S. and Hagras, H., (2013). A general type-2 Fuzzy Logic based Multi-Criteria group decision making for lighting level selection in an intelligent environment

Bilgin, A., Dooley, J., Whittington, L., Hagras, H., Henson, M., Wagner, C., Malibari, A., Al-Ghamdi, A., Alhaddad, MJ. and Alghazzawi, D., (2012). Dynamic Profile-Selection for zSlices based type-2 fuzzy agents controlling multi-user Ambient Intelligent Environments

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2012). Towards a general type-2 fuzzy logic approach for Computing With Words using linear adjectives

Kassem, S., Hagras, H., Owusu, G. and Shakya, S., (2012). A type2 Fuzzy Logic System for workforce management in the telecommunications domain

Sahab, N. and Hagras, H., (2012). Towards comparing adaptive type-2 input based non-singleton type-2 FLS and non-singleton FLSs employing Gaussian inputs

Naim, S., Hagras, H. and Garibaldi, JM., (2012). A fuzzy logic based Multi-criteria Group Decision Making system for the assesement of umbilical cord acid-base balance

Naim, S. and Hagras, H., (2012). A hybrid approach for Multi-Criteria Group Decision Making based on interval type-2 fuzzy logic and Intuitionistic Fuzzy evaluation

Bernardo, D., Hagras, H. and Tsang, E., (2012). An interval type-2 Fuzzy Logic based system for model generation and summarization of arbitrage opportunities in stock markets

(2012). Autonomous and Intelligent Systems

Bernardo, D., Hagras, H. and Tsang, E., (2012). An Interval Type-2 Fuzzy Logic System for the Modeling and Prediction of Financial Applications

Mohamed, A., Hagras, H., Shakya, S. and Owusu, G., (2012). Tactical Resource Planner for Workforce Allocation in Telecommunications

Yao, B., Hagras, H., Ghazzawi, DA. and Alhaddad, MJ., (2012). An Interval Type-2 Fuzzy Logic System for Human Silhouette Extraction in Dynamic Environments

Huang, H-D., Lee, C-S., Hagras, H. and Kao, H-Y., (2012). TWMAN+: A Type-2 fuzzy ontology model for malware behavior analysis

Bilgin, A., Hagras, H., Malibari, A., Alhaddad, MJ. and Alghazzawi, D., (2012). A general type-2 fuzzy logic approach for adaptive modeling of perceptions for Computing With Words

Bosnak, M. and Blazic, S., (2012). Sparse VSLAM with Camera-Equipped Quadrocopter.

Abghari, A., Abida, K. and Karray, F., (2012). Features' Weight Learning towards Improved Query Classification.

Silva, A., Neves, A. and Gonçalves, T., (2012). An Heterogeneous Particle Swarm Optimizer with Predator and Scout Particles.

Mittal, A., Sofat, S. and Hancock, ER., (2012). Detection of Edges in Color Images: A Review and Evaluative Comparison of State-of-the-Art Techniques.

Mittal, A., Sofat, S. and Hancock, ER., (2012). An Efficient Scheme for Color Edge Detection in Uniform Color Space.

Siddiqui, JR. and Lindley, C., (2012). Multi-Cue Based Place Learning for Mobile Robot Navigation.

Wang, L., Yang, SX. and Biglarbegian, M., (2012). Bio-inspired Navigation of Mobile Robots.

Khaki, K. and Stonham, TJ., (2012). Face Recognition with Weightless Neural Networks Using the MIT Database.

Mirabdollah, MH. and Mertsching, B., (2012). Bearing Only SLAM: A New Particle Filter Based Approach.

Guedea-Elizalde, F. and Villegas-Hernandez, YS., (2012). Automatic Planning in a Robotized Cell.

Zhu, J. and Gueaieb, W., (2012). Adaptive Fuzzy Logic Control for Time-Delayed Bilateral Teleoperation.

Sun, J., Sun, J., Abida, K. and Karray, F., (2012). A Novel Template Matching Approach to Speaker-Independent Arabic Spoken Digit Recognition.

Ripon, KSN., Glette, K., Høvin, M. and Tørresen, J., (2012). Job Shop Scheduling with Transportation Delays and Layout Planning in Manufacturing Systems: A Multi-objective Evolutionary Approach.

Ven, OSVD., Yang, R., Xia, S., Schieveen, JPV., Spronck, JW., Schmidt, RHM. and Nihtianov, SN., (2012). Autonomous Self-aligning and Self-calibrating Capacitive Sensor System.

Lanza-Gutiérrez, JM., Pulido, JAG., Vega-Rodríguez, MA. and Sánchez-Pérez, JM., (2012). Relay Node Positioning in Wireless Sensor Networks by Means of Evolutionary Techniques.

Kurowski, M., Korte, H. and Lampe, BP., (2012). Search-and-Rescue-Operation with an Autonomously Acting Rescue Boat.

Filho, CFFC., Melo, RDO. and Costa, MGF., (2012). Detecting Natural Gas Leaks Using Digital Images and Novelty Filters.

Elmogy, AM., Khamis, AM. and Karray, F., (2012). Market-Based Framework for Mobile Surveillance Systems.

Idris, M., Mehrabian, A., Hamou-Lhadj, A. and Khoury, R., (2012). Pattern-Based Trace Correlation Technique to Compare Software Versions.

Frattini, F., Esposito, M. and Pietro, GD., (2012). MobiFuzzy: A Fuzzy Library to Build Mobile DSSs for Remote Patient Monitoring.

Alves, FS., Dias, RA., Cabral, J. and Rocha, LA., (2012). Autonomous MEMS Inclinometer.

Alemzadeh, M., Abida, K., Khoury, R. and Karray, F., (2012). Enhancement of the ROVER's Voting Scheme Using Pattern Matching.

Abida, K., Karray, F. and Abida, W., (2012). A Novel Voting Scheme for ROVER Using Automatic Error Detection.

Ros, M., Delgado, M., Vila, A., Hagras, H. and Bilgin, A., (2012). A fuzzy logic approach for learning daily human activities in an Ambient Intelligent Environment

Golestan, K., Jundi, A., Nassar, L., Sattar, F., Karray, F., Kamel, MS. and Boumaiza, S., (2012). Vehicular Ad-hoc Networks(VANETs): Capabilities, Challenges in Information Gathering and Data Fusion.

Alhaddad, MJ., Kamel, M., Malibary, H., Thabit, K., Dahlwi, F. and Hadi, A., (2012). P300 Speller Efficiency with Common Average Reference.

Nassar, L., Jundi, A., Golestan, K., Sattar, F., Karray, F., Kamel, MS. and Boumaiza, S., (2012). Vehicular Ad-hoc Networks(VANETs): Capabilities, Challenges in Context-Aware Processing and Communication Gateway.

Teófilo, LF., Passos, N., Reis, LP. and Cardoso, HL., (2012). Adapting Strategies to Opponent Models in Incomplete Information Games: A Reinforcement Learning Approach for Poker.

Voulkidis, AC., Livieratos, SN. and Cottis, PG., (2012). Spatially Correlated Multi-modal Wireless Sensor Networks: A Coalitional Game Theoretic Approach.

Garcia-Valverde, T., Garcia-Sola, A., Gomez-Skarmeta, A., Botia, JA., Hagras, H., Dooley, J. and Callaghan, V., (2012). An adaptive learning fuzzy logic system for indoor localisation using Wi-Fi in Ambient Intelligent Environments

Yao, B., Hagras, H., Ghanbari, M., Alhaddad, M. and Alghazzawi, D., (2012). Type-2 Fuzzy Logic Approach for Detecting Human Related Events in Videos

Wagner, C. and Hagras, H., (2011). Interpreting fuzzy set operations and Multi Level Agreement in a Computing with Words context

Hagras, H., (2011). Towards Online Adaptive Ambient Intelligent Environments for Multiple Occupants

Dooley, J., Callaghan, V., Hagras, H., Gardner, M., Ghanbari, M. and Al-Ghazzawi, D., (2011). The Intelligent Classroom : Beyond Four Walls

Sahab, N. and Hagras, H., (2011). An adaptive type-2 input based nonsingleton type-2 Fuzzy Logic System for real world applications

Wagner, C. and Hagras, H., (2011). Employing zSlices based general type-2 fuzzy sets to model multi level agreement

Sahab, N. and Hagras, H., (2011). A Type-2 Nonsingleton Type-2 Fuzzy Logic System to Handle Linguistic and Numerical Uncertainties in Real World Environments

Almehdar, M. and Hagras, H., (2011). An adaptive type-2 fuzzy based charging technique for market design agents in uncertain environments

Dooley, J., Wagner, C., Hagras, H. and Pruvost, G., (2011). FollowMe: The Persistent GUI

Cara, AB., Rojas, I., Pomares, H., Wagner, C. and Hagras, H., (2011). On comparing non-singleton type-1 and singleton type-2 fuzzy controllers for a nonlinear servo system

Lee, C-S., Wang, M-H., Chen, Y-J. and Hagras, H., (2011). Fuzzy Markup Language for game of NoGo

Dooley, J., Henson, M., Callaghan, V., Hagras, H., Al-Ghazzawi, D., Malibari, A., Al-Haddad, M. and Al-Ghamdi, AA-M., (2011). A Formal Model for Space Based Ubiquitous Computing

Helal, S., Lee, JW., Hossain, S., Kim, E., Hagras, H. and Cook, D., (2011). Persim - Simulator for Human Activities in Pervasive Spaces

Ibrahim, M., Khairy, A., Hagras, H., Abdel-Rahim, N., Shafei, AE. and Shaltout, A., (2011). Intelligent energy management strategy for decentralized battery storage in grid connected wind energy conversion systems

Al Mehdar, M. and Hagras, H., (2011). An Adaptive Type-2 Fuzzy Based Charging Technique for Market Design Agents in Uncertain Environments

Sahab, N. and Hagras, H., (2011). An Adaptive Type-2 Input Based Nonsingleton Type-2 Fuzzy Logic System for Real World Applications

Dooley, J., Henson, M., Callaghan, V., Hagras, H., Al-Ghazzawi, D., Malibari, A., Al-Haddad, M. and Al-Ghamdi, AA., (2011). A Formal Model for Space Based Ubiquitous Computing

Naim, S. and Hagras, H., (2011). Type-2 Fuzzy Logic in Multi-Criteria Group Decision Making with Intuitionistic Evaluation

Almeida, M., Moreira, N. and Reis, R., (2011). Incremental DFA Minimisation

Wagner, C. and Hagras, H., (2010). An approach for the generation and adaptation of zSlices based general type-2 fuzzy sets from interval type-2 fuzzy sets to model agreement with application to Intelligent Environments

Wagner, C. and Hagras, H., (2010). Fuzzy Composite Concepts based on human reasoning

Almehdar, M. and Hagras, H., (2010). An intelligent fuzzy based system for market design agents

Zaher, M. and Hagras, H., (2010). Data generated type-2 fuzzy logic model for control of wind turbines

Zaher, M., Hagras, H., Khairy, A. and Ibrahim, M., (2010). A type-2 fuzzy logic based model for renewable wind energy generation

Ibrahim, M., Khairy, A., Hagras, H. and Zaher, M., (2010). Using a fuzzy agent in modeling lead-acid battery operating in grid connected wind energy conversion systems

Hagras, H., Ramadan, R., Nawito, M., Gabr, H., Zaher, M. and Fahmy, H., (2010). A fuzzy based hierarchical coordination and control system for a robotic agent team in the robot Hockey competition

Elfaham, A., Hagras, H., Helal, S., Hossain, S., Lee, JW. and Cook, D., (2010). A fuzzy based verification agent for the Persim human activity simulator in Ambient Intelligent Environments

Ramadan, RA., Hagras, H., Nawito, M., Faham, AE. and Eldesouky, B., (2010). The Intelligent Classroom: Towards an Educational Ambient Intelligence Testbed

Dooley, J., Callaghan, V., Hagras, H. and Bull, P., (2010). Simpleware Device Surrogates: Enabling High-Level Description and Interaction with Resource Constrained Devices

Dooley, J., Davies, M., Ball, M., Callaghan, V., Hagras, H., Colley, MJ. and Gardner, M., (2010). Decloaking Big Brother: Demonstrating Intelligent Environments

Wagner, C. and Hagras, H., (2010). A collection operator for type-2 fuzzy logic systems

(2010). [Front matter]

Wagner, C. and Hagras, H., (2010). Uncertainty and type-2 fuzzy sets and systems

Sahab, N. and Hagras, H., (2010). A hybrid approach to modeling input variables in non-singleton type-2 Fuzzy Logic Systems

Azouz, M., Shaltout, A., Elshafei, MAL., Abdel-Rahim, M., Hagras, H., Zaher, M. and Ibrahim, M., (2010). Fuzzy Logic Control of Wind Energy Systems

Ibrahim, M., Khairy, A., Hagras, H., Zaher, M., El Shafei, A., Shaltout, A. and Rehim, NA., (2010). Studying the Effect of Decentralized Battery Storage to Smooth the Generated Power of a Grid Integrated Wind Energy Conversion System

Dooley, J., Callaghan, V., Hagras, H. and Bull, P., (2009). Discovering the home: Advanced concepts

Dooley, J., Callaghan, V., Hagras, H. and Bull, P., (2009). Discovering the Home

Wagner, C. and Hagras, H., (2009). zSlices based general type-2 FLC for the control of autonomous mobile robots in real world environments

Wagner, C. and Hagras, H., (2009). Novel methods for the design of general type-2 fuzzy sets based on device characteristics and linguistic labels surveys

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2009). A neuro-fuzzy based agent for group decision support in applicant ranking within human resources systems

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2009). A fuzzy based agent for group decision support of applicants ranking within recruitment systems

Kameas, AD., Goumopoulos, C., Hagras, H., Callaghan, V., Heinroth, T. and Weber, M., (2009). An Architecture That Supports Task-Centered Adaptation In Intelligent Environments

Lee, C-S., Wang, M-H., Hsu, C-Y. and Hagras, H., (2009). A Novel Type-2 Fuzzy Ontology and Its Application to Diet Assessment

Kameas, A., Goumopoulos, C., Hagras, H., Gardner, M., Heinroth, T., Minker, W., Meliones, A., Economou, D., Bellik, Y. and Pruvost, G., (2009). A Pervasive System Architecture That Supports Adaptation Using Agents and Ontologies

Elkasrawy, S., Hagras, H. and Nawito, M., (2009). An Intelligent System for Extracting Intro and Outre Times in Songs Using Artificial Neural Networks

El-Faham, A. and Hagras, H., (2009). A Speech Recognizer Based Intelligent Agent For Ambient Intelligent Environments

El-Desouky, B. and Hagras, H., (2009). An Adaptive Type-2 Fuzzy Logic Based Agent for Multi-Occupant Ambient Intelligent Environments

Mowafey, S., Schmitt, A., Hagras, H. and Minker, W., (2009). Creating an Ambient Intelligent Environment with an Emotion-Aware System

Bellik, Y., Kameas, A., Goumopoulos, C., Hagras, H., Heinroth, T., Pruvost, G., Meliones, A., Economou, D., Minker, W. and Gardner, M., (2009). Multidimensional Pervasive Adaptation into Ambient Intelligent Environments

Heinroth, T., Kameas, A., Hagras, H. and Bellik, Y., (2009). Semi-tacit Adaptation of Intelligent Environments

(2009). [Front matter]

Wagner, C. and Hagras, H., (2009). Employing Interpolation to enable the operation High Order Fuzzy Systems on Embedded Systems

Kameas, A., Hagras, H., Goumopoulos, C., Heinroth, T., Meliones, A., Gardner, M., Economou, D., Pruvost, G., Bellik, Y. and Minker, W., (2009). Pervasive System Architecture that supports Adaptation using Agents and Ontologies

Wagner, C. and Hagras, H., (2008). zSlices — towards bridging the gap between interval and general type-2 fuzzy logic

Doctor, F., Hagras, H., Roberts, D. and Callaghan, V., (2008). A type-2 fuzzy based system for handling the uncertainties in group decisions for ranking job applicants within Human Resources systems

Hagras, H., (2008). Developing a type-2 FLC through embedded type-1 FLCs

Hagras, H., (2008). Type-2 Fuzzy Logic Controllers: A Way Forward for Fuzzy Systems in Real World Environments

Hagras, H., Packharn, I., Vanderstockt, Y., McNulty, N., Vadher, A. and Doctor, F., (2008). An intelligent agent based approach for energy management in commercial buildings

Goumopoulos, C., Kameas, A., Hagras, H., Callaghan, V., Gardner, M., Minker, W., Weber, Bellik, Y. and Meliones, A., (2008). ATRACO: Adaptive and Trusted Ambient Ecologies

Jammeh, E., Fleury, M., Wagner, C., Hagras, H. and Ghanbari, M., (2008). Interval type-2 fuzzy logic congestion control of video streaming

Wagner, C. and Hagras, H., (2007). A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots

Wagner, C. and Hagras, H., (2007). Evolving Type-2 Fuzzy Logic Controllers for Autonomous Mobile Robots

Duman, H., Hagras, H. and Callaghan, V., (2007). A Fuzzy Based Architecture for Learning Relevant Embedded Agents Associations in Ambient Intelligent Environments

Lynch, C., Hagras, H. and Callaghan, V., (2007). Parallel Type-2 Fuzzy Logic Co-Processors for Engine Management

Wagner, C. and Hagras, H., (2007). A Genetic Algorithm Based Architecture for Evolving Type-2 Fuzzy Logic Controllers for Real World Autonomous Mobile Robots.

Duman, H., Hagras, H. and Callaghan, V., (2007). A Fuzzy Based Architecture for Learning Relevant Embedded Agents Associations in Ambient Intelligent Environments.

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2006). Automated Discovery of Human Activities inside Pervasive Living Spaces

Lynch, C., Hagras, H. and Callaghan, V., (2006). Using Uncertainty Bounds in the Design of an Embedded Real-Time Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines

Hagras, H., Doctor, F., Lopez, A. and Callaghan, V., (2006). Evolving Type-2 Fuzzy Agents for Ambient Intelligent Environments

Tawil, E. and Hagras, H., (2006). An Adaptive Genetic-Based Architecture for the On-line Co-ordination of Fuzzy Embedded Agents with Multiple Objectives and Constraints

Doctor, F., Hagras, H. and Callaghan, V., (2006). Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments

Hagras, H., Colley, M., Pounds-Cornish, A., De Souza, G., Callaghan, V., Nikiforidis, G., Argyropoulos, C., Kameas, A. and Murphy, F., (2006). A Collaborating Team of Spiking Neural Network Based Robotic Agents for Inaccessible Fluidic Environments

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2006). Towards the detection of temporal behavioural patterns in intelligent environments

Dooley, J., Callaghan, V., Hagras, H., Bull, P. and Rohlfing, D., (2006). Ambient intelligence - knowledge representation, processing and distribution in intelligent inhabited environments

O'Flynn, B., Murphy, F., Buckley, J., Laffey, D., Barton, J., Hagras, H., Colley, M. and Pounds-Cornish, A., (2006). SOCIAL -Collaborative agent development

Lynch, C., Hagras, H. and Callaghan, V., (2006). Embedded Interval Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines

Chin, JSY., Callaghan, LV., Clarke, G., Hagras, H. and Colley, M., (2005). End-user programming in pervasive computing environments

Lynch, C., Hagras, H. and Callaghan, V., (2005). Embedded type-2 FLC for real-time speed control of marine & traction diesel engines

Tawil, E. and Hagras, H., (2005). Adaptive on-line co-ordination of ubiquitous computing devices with multiple objectives and constraints

Lopez, A., Alvarez, D., Doctor, F., Hagras, H. and Callaghan, V., (2005). A comparison of some data-based methods for the off-line generation of fuzzy logic controllers for an intelligent building environment

Limb, PR., Armitage, S., Chin, JSY., Kalawsky, R., Callaghan, V., Bull, PM., Hagras, H. and Colley, M., (2005). User interaction in a shared information space - a pervasive environment for the home

Hagras, H. and Colley, M., (2005). Collaborating multi robotic agents for operations in inaccessible environments

Chin, JSY., Callaghan, V., Colley, M., Hagras, H. and Clarke, G., (2005). Virtual appliances for pervasive computing: A deconstructionist, ontology based, programming-by-example approach

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2005). A neural network agent based approach to activity detection in AmI environments

Tawil, E. and Hagras, H., (2004). A novel multi-objective multi-constraint genetic algorithms approach for Co-ordinating embedded agents

Doctor, F., Hagras, H. and Callaghan, V., (2004). A type-2 fuzzy embedded agent for ubiquitous computing environments

Doctor, F., Hagras, H., Callaghan, V. and Lopez, A., (2004). An adaptive fuzzy learning mechanism for intelligent agents in ubiquitous computing environments

Hagras, H., (2004). A type-2 fuzzy logic controller for autonomous mobile robots

Tawil, E. and Hagras, H., (2004). An adaptive multi embedded-agent architecture for intelligent inhabited environments

Colley, M., de Souza, G., Hagras, H., Pounds-Cornish, A., Clarke, G. and Callaghan, V., (2004). Towards developing micro-scale robots for inaccessible fluidic environments

Rivera-Illingworth, F., Callaghan, V. and Hagras, H., (2004). A counectionist embeddled agent approach for abnormal behaviour detection in intelligent health care environments

Hagras, H., Pounds-Cornish, A., Colley, M., Callaghan, V. and Clarke, G., (2004). Evolving spiking neural network controllers for autonomous robots

Lopez, A., Sanchez, L., Doctor, F., Hagras, H. and Callaghan, V., (2004). An evolutionary algorithm for the off-line data driven generation of fuzzy controllers for intelligent buildings

Bellis, S., Razeeb, KM., Saha, C., Delaney, K., O'Mathuna, C., Pounds-Cornish, A., de Souza, G., Colley, M., Hagras, H., Clarke, G., Callaghan, V., Argyropoulos, C., Karistianos, C. and Nikiforidis, G., (2004). FPGA implementation of spiking neural networks - an initial step towards building tangible collaborative autonomous agents

Hagras, H., Callaghan, V., Colley, M., Clarke, G. and Duman, H., (2003). Online Learning and Adaptation for Intelligent Embedded Agents Operating in Domestic Environments

Hagras, H., (2003). A hierarchical fuzzy–genetic multi-agent architecture for intelligent buildings online learning, adaptation and control

Hagras, H., Colley, M., Callaghan, V., Clarke, G., Duman, H. and Holmes, A., (2002). A fuzzy incremental synchronous learning technique for embedded-agents learning and control in intelligent inhabited environments

Hagras, H., Colley, M. and Callaghan, V., (2001). Life long learning and adaptation for embedded agents operating in unstructured environments

Hagras, H., Callaghan, V., Colley, M. and Clarke, G., (2001). A Hierarchical Fuzzy Genetic Multi-Agent Architecture for Intelligent Buildings Sensing and Control

Hagras, H., Callaghan, V. and Colley, M., (2000). An embedded-agent architecture for online learning & control in intelligent machines

Hagras, H., Callaghan, V. and Colley, M., (2000). Online learning of the sensors fuzzy membership functions in autonomous mobile robots

Hagras, H., Callaghan, V. and Colley, M., (2000). Online learning of fuzzy behaviour co-ordination for autonomous agents using genetic algorithms & real-time interaction with the environment

Hagras, H., Callaghan, V., Colley, M. and Carr-West, M., (1999). Fuzzy-genetic based embedded-agent approach to learning & control in agricultural autonomous vehicles

Hagras, H., Callaghan, V., Colley, M. and Carr-West, M., (1999). A behaviour based hierarchical fuzzy control architecture for agricultural autonomous mobile robots

Hagras, H., Callaghan, V., Colley, MJ. and Carr-West, M., (1999). Developing an Outdoor Fuzzy Logic Controlled Agricultural Vehicle for Crop Following and Harvesting.

Hagras, H., Callaghan, V. and Colley, M., (1999). Online learning of fuzzy behaviours using genetic algorithms and real-time interaction with the environment