| Bayesian hierarchical models for aerospace gas turbine engine prognostics MA Zaidan, RF Harrison, AR Mills, PJ Fleming Expert Systems with Applications 42 (1), 539-553, 2015 | 49 | 2015 |
| Gas turbine engine prognostics using Bayesian hierarchical models: A variational approach MA Zaidan, AR Mills, RF Harrison, PJ Fleming Mechanical Systems and Signal Processing 70, 120-140, 2016 | 42 | 2016 |
| Bayesian framework for aerospace gas turbine engine prognostics MA Zaidan, AR Mills, RF Harrison 2013 IEEE Aerospace Conference, 1-8, 2013 | 26 | 2013 |
| Prognostics of gas turbine engine: An integrated approach MA Zaidan, R Relan, AR Mills, RF Harrison Expert Systems with Applications 42 (22), 8472-8483, 2015 | 22 | 2015 |
| Dynamic modelling and control of a twin-rotor system using adaptive neuro-fuzzy inference system techniques M Omar, MA Zaidan, MO Tokhi Proceedings of the Institution of Mechanical Engineers, Part G: Journal of …, 2012 | 9 | 2012 |
| Modelling of a flexible manoeuvring system using ANFIS techniques M Omar, MA Zaidan, MO Tokhi 2010 12th International Conference on Computer Modelling and Simulation, 33-38, 2010 | 8 | 2010 |
| Fusing an ensemble of diverse prognostic life predictions OW Laslett, AR Mills, MA Zaidan, RF Harrison 2014 IEEE Aerospace Conference, 1-10, 2014 | 7 | 2014 |
| Megasense: Feasibility of low-cost sensors for pollution hot-spot detection E Lagerspetz, NH Motlagh, MA Zaidan, PL Fung, J Mineraud, S Varjonen, ... Proceedings of the 2019 IEEE 17th International Conference on Industrial …, 2019 | 6 | 2019 |
| Exploring non-linear associations between atmospheric new-particle formation and ambient variables: a mutual information approach MA Zaidan, V Haapasilta, R Relan, P Paasonen, VM Kerminen, ... Atmospheric Chemistry and Physics 18 (17), 12699-12714, 2018 | 6 | 2018 |
| Accommodating repair actions into gas turbine prognostics Z Skaf, MA Zaidan, RF Harrison, AR Mills PHM Society, 2013 | 6 | 2013 |
| Curating scientific information in knowledge infrastructures M Stocker, P Paasonen, M Fiebig, MA Zaidan, A Hardisty | 5 | 2018 |
| Neural network classifier on time series features for predicting atmospheric particle formation days MA Zaidan, V Haapsilta, R Relan, H Junninen, P Aalto, FF Canova, ... Proceedings of the 20th International Conference on Nucleation and …, 2017 | 4 | 2017 |
| Mixture of Clustered Bayesian Neural Networks for Modeling Friction Processes at the Nanoscale MA Zaidan, FF Canova, L Laurson, AS Foster Journal of chemical theory and computation 13 (1), 3-8, 2017 | 4 | 2017 |
| The Adaptive Control of FES-assisted Indoor Rowing Exercise Z Hussain, MA Zaidan, MO Tokhi, R Jailani Proceedings of 2009 CACS International Automatic Control Conference, 2009 | 4 | 2009 |
| Indoor air quality monitoring using infrastructure-based motion detectors NH Motlagh, MA Zaidan, E Lagerspetz, S Varjonen, J Toivonen, ... Proceedings of the 2019 IEEE 17th International Conference on Industrial …, 2019 | 3 | 2019 |
| Prognostics of lithium-ion batteries using a deterministic Bayesian approach F Zheng, J Jiang, MA Zaidan, W He, M Pecht 2015 IEEE Conference on Prognostics and Health Management (PHM), 1-4, 2015 | 3 | 2015 |
| An on-line approach for ANFIS modelling and control of a flexible manoeuvring system M Omar, M Mohamad, MA Zaidan, MO Tokhi 2011 IEEE International Conference on Mechatronics, 324-329, 2011 | 3 | 2011 |
| Mutual information input selector and probabilistic machine learning utilisation for air pollution proxies MA Zaidan, L Dada, MA Alghamdi, H Al-Jeelani, H Lihavainen, ... Applied Sciences 9 (20), 4475, 2019 | 2 | 2019 |
| Predicting atmospheric particle formation days by Bayesian classification of the time series features MA Zaidan, V Haapasilta, R Relan, H Junninen, PP Aalto, M Kulmala, ... Tellus B: Chemical and Physical Meteorology 70 (1), 1-10, 2018 | 2 | 2018 |
| Bayesian approaches for complex system prognostics Zaidan, Martha A University of Sheffield, 2014 | 2 | 2014 |
Andrew R MillsUniversity of SheffieldVerified email at sheffield.ac.uk
