| Unsupervised anomaly detection with LSTM autoencoders using statistical data-filtering S Maleki, S Maleki, NR Jennings Applied Soft Computing 108, 107443, 2021 | 97 | 2021 |
| Development and Realisation of Changepoint Analysis for the Detection of Emerging Faults on Industrial Systems S Maleki, C Bingham, Y Zhang IEEE Transactions on Industrial Informatics 12 (3), 1180-1187, 2016 | 32 | 2016 |
| Failure identification for 3D linear systems S Maleki, P Rapisarda, L Ntogramatzidis, E Rogers Multidimensional Systems and Signal Processing 26, 481-502, 2015 | 12 | 2015 |
| A geometric approach to 3D fault identification S Maleki, P Rapisarda, L Ntogramatzidis, E Rogers nDS'13; Proceedings of the 8th International Workshop on Multidimensional …, 2013 | 9 | 2013 |
| Performance analysis of a twin-shaft gas turbine with fault in the variable stator guide vane system of the axial compressor S Cruz-Manzo, S Maleki, V Panov, F Agbonzikilo, Y Zhang, A Latimer Proceedings of the 9th International Gas Turbine Conference, Brussels …, 2018 | 6 | 2018 |
| Analysis of performance of a twin-shaft gas turbine during hot-end damage in the gas generator turbine S Cruz-Manzo, S Maleki, V Panov, F Agbonzikilo, Y Zhang, A Latimer Turbo Expo: Power for Land, Sea, and Air 51128, V006T05A010, 2018 | 6 | 2018 |
| Robust hierarchical clustering for novelty identification in sensor networks: With applications to industrial systems S Maleki, C Bingham Applied Soft Computing 85, 105771, 2019 | 5 | 2019 |
| Performance analysis of a twin shaft Industrial Gas Turbine at fouling conditions S Cruz-Manzo, S Maleki, Y Zhang, V Panov, A Latimer 2017 IEEE International Conference on Prognostics and Health Management …, 2017 | 5 | 2017 |
| Failure identification for linear repetitive processes S Maleki, P Rapisarda, E Rogers Multidimensional Systems and Signal Processing 26, 1037-1059, 2015 | 5 | 2015 |
| A one-class clustering technique for novelty detection and isolation in sensor networks S Maleki, C Bingham 2017 IEEE International Conference on Computational Intelligence and Virtual …, 2017 | 4 | 2017 |
| Model-based compensation of sensor failure in industrial gas turbine V Panov, S Maleki Proceedings of the 1st Global Power and Propulsion Forum, GPPF, 2017 | 3 | 2017 |
| Operational pattern analysis for predictive maintenance scheduling of industrial systems Y Zhang, C Bingham, M Gallimore, S Maleki IEEE International Conference on Computational Intelligence and Virtual …, 2015 | 3 | 2015 |
| Review evolution of dual-resource-constrained scheduling problems in manufacturing systems: modeling and scheduling methods’ trends A Delgoshaei, MKAM Ariffin, S Maleki, Z Leman Soft Computing 27 (24), 18489-18528, 2023 | 1 | 2023 |
| Performance analysis and prediction of compressor fouling condition for a twin-shaft engine S Maleki, S Cruz-Manzo, C Bingham, V Panov GPPS-2018-035, 2nd Global Power and Propulsion Forum 2018, 10–12 Jan, 2018 …, 2018 | 1 | 2018 |
| A geometric approach to fault identification in linear repetitive processes S Maleki, Z Shang, P Rapisarda | 1 | 2014 |
| C (NN) FD--deep learning predictions of tip clearance variations on multi-stage axial compressors aerodynamic performance G Bruni, S Maleki, SK Krishnababu arXiv preprint arXiv:2310.04264, 2023 | | 2023 |
| Deep learning modelling of tip clearance variations on multi-stage axial compressors aerodynamics G Bruni, S Maleki, SK Krishnababu arXiv e-prints, arXiv: 2310.04264, 2023 | | 2023 |
| C (NN) FD--a deep learning framework for turbomachinery CFD analysis G Bruni, S Maleki, SK Krishnababu arXiv preprint arXiv:2306.05889, 2023 | | 2023 |
| Performance analysis of a twin-shaft gas turbine with fault in the variable stator guide vane system of the axial compressor A Latimer, F Agbonzikilo, S Cruz-Manzo, S Maleki, V Panov, Y Zhang University of Lincoln, 2018 | | 2018 |
| Performance analysis and prediction of compressor fouling condition for a twin-shaft engine C Bingham, S Cruz-Manzo, S Maleki, V Panov University of Lincoln, 2018 | | 2018 |
Paolo RapisardaFull Professor, University of SouthamptonEmail verificata su ecs.soton.ac.uk
