| Detecting sensor faults, anomalies and outliers in the internet of things: A survey on the challenges and solutions A Gaddam, T Wilkin, M Angelova, J Gaddam Electronics 9 (3), 511, 2020 | 184 | 2020 |
| Weakly monotone averaging functions T Wilkin, G Beliakov, T Calvo Information Processing and Management of Uncertainty in Knowledge-Based …, 2014 | 123 | 2014 |
| Weakly monotonic averaging functions T Wilkin, G Beliakov International Journal of Intelligent Systems 30 (2), 144-169, 2014 | 110 | 2014 |
| Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews SD Tagliaferri, M Angelova, X Zhao, PJ Owen, CT Miller, T Wilkin, ... NPJ digital medicine 3 (1), 93, 2020 | 98 | 2020 |
| Vector valued similarity measures for Atanassov’s intuitionistic fuzzy sets G Beliakov, M Pagola, T Wilkin Information Sciences 280, 352-367, 2014 | 63 | 2014 |
| Anomaly detection models for detecting sensor faults and outliers in the IoT-a survey A Gaddam, T Wilkin, M Angelova 2019 13th International Conference on Sensing Technology (ICST), 1-6, 2019 | 38 | 2019 |
| Three types of monotonicity of averaging functions G Beliakov, T Calvo, T Wilkin Knowledge-Based Systems 72, 114-122, 2014 | 38 | 2014 |
| A case study in knowledge discovery and elicitation in an intelligent tutoring application A Nicholson, T Boneh, T Wilkin, K Stacey, L Sonenberg, V Steinle arXiv preprint arXiv:1301.2297, 2013 | 31 | 2013 |
| Weakly monotone aggregation functions T Wilkin, G Beliakov Int. J. Intell. Syst 30, 144-165, 2015 | 30 | 2015 |
| On the weak monotonicity of Gini means and other mixture functions G Beliakov, T Calvo, T Wilkin Information Sciences 300, 70-84, 2015 | 28 | 2015 |
| On some properties of weighted averaging with variable weights G Beliakov, T Wilkin Information Sciences 281, 1-7, 2014 | 20 | 2014 |
| Image reduction operators based on non-monotonic averaging functions T Wilkin 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2013 | 20 | 2013 |
| Aggregation and consensus for preference relations based on fuzzy partial orders G Beliakov, S James, T Wilkin Fuzzy Optimization and Decision Making 16, 409-428, 2017 | 17 | 2017 |
| Robustifying OWA operators for aggregating data with outliers G Beliakov, S James, T Wilkin, T Calvo IEEE Transactions on Fuzzy Systems 26 (4), 1823-1832, 2017 | 17 | 2017 |
| Characterizing compactness of geometrical clusters using fuzzy measures G Beliakov, G Li, HQ Vu, T Wilkin IEEE Transactions on Fuzzy Systems 23 (4), 1030-1043, 2015 | 16 | 2015 |
| Evaluating sensor placement and modality for activity recognition in active games N Jablonsky, S McKenzie, S Bangay, T Wilkin Proceedings of the Australasian Computer Science Week Multiconference, 1-8, 2017 | 15 | 2017 |
| A weighted matrix visualization for fuzzy measures and integrals AR Buck, DT Anderson, JM Keller, T Wilkin, MA Islam 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2020 | 14 | 2020 |
| Chronic back pain sub-grouped via psychosocial, brain and physical factors using machine learning SD Tagliaferri, T Wilkin, M Angelova, BM Fitzgibbon, PJ Owen, CT Miller, ... Scientific reports 12 (1), 15194, 2022 | 13 | 2022 |
| Adaptive control of the closed loop behaviour of manufacturing processes T Wilkin, Y Frayman, B Rolfe Engineering Systems Design and Analysis 42509, 313-321, 2006 | 13 | 2006 |
| Information fusion-2-text: Explainable aggregation via linguistic protoforms BJ Murray, DT Anderson, TC Havens, T Wilkin, A Wilbik Information Processing and Management of Uncertainty in Knowledge-Based …, 2020 | 10 | 2020 |
Gleb BeliakovDeakin UniversityVerified email at deakin.edu.au
