| Nuclear power plant components condition monitoring by probabilistic support vector machine J Liu, R Seraoui, V Vitelli, E Zio Annals of Nuclear Energy 56, 23-33, 2013 | 56 | 2013 |
| A SVM framework for fault detection of the braking system in a high speed train J Liu, YF Li, E Zio Mechanical Systems and Signal Processing 87, 401-409, 2017 | 39 | 2017 |
| System dynamic reliability assessment and failure prognostics J Liu, E Zio Reliability Engineering & System Safety 160, 21-36, 2017 | 29 | 2017 |
| An adaptive online learning approach for Support Vector Regression: Online-SVR-FID J Liu, E Zio Mechanical Systems and Signal Processing 76, 796-809, 2016 | 28 | 2016 |
| A novel dynamic-weighted probabilistic support vector regression-based ensemble for prognostics of time series data J Liu, V Vitelli, E Zio, R Seraoui IEEE Transactions on Reliability 64 (4), 1203-1213, 2015 | 26 | 2015 |
| A SVR-based ensemble approach for drifting data streams with recurring patterns J Liu, E Zio Applied Soft Computing 47, 553-564, 2016 | 12 | 2016 |
| SVM hyperparameters tuning for recursive multi-step-ahead prediction J Liu, E Zio Neural Computing and Applications, 1-15, 2016 | 12 | 2016 |
| Integration of feature vector selection and support vector machine for classification of imbalanced data J Liu, E Zio Applied Soft Computing 75, 702-711, 2019 | 11 | 2019 |
| A scalable fuzzy support vector machine for fault detection in transportation systems J Liu, E Zio Expert Systems with Applications 102, 36-43, 2018 | 10 | 2018 |
| Feature vector regression with efficient hyperparameters tuning and geometric interpretation J Liu, E Zio Neurocomputing 218, 411-422, 2016 | 8 | 2016 |
| Dynamic reliability assessment and prognostics with monitored data for multiple dependent degradation components J Liu, E Zio European Safety and Reliability Conference, 2016 | 8 | 2016 |
| Weighted-feature and cost-sensitive regression model for component continuous degradation assessment J Liu, E Zio Reliability Engineering & System Safety 168, 210-217, 2017 | 6 | 2017 |
| Dynamic weighted PSVR-based ensembles for prognostics of nuclear components J Liu, V Vitelli, R Seraoui, E Zio FLINS 2014, 2014 | 6 | 2014 |
| Prediction of peak values in time series data for prognostics of critical components in nuclear power plants J Liu, E Zio IFAC-PapersOnLine 49 (28), 174-178, 2016 | 5 | 2016 |
| Prognostics of a multistack PEMFC system with multiagent modeling J Liu, E Zio Energy Science & Engineering 7 (1), 76-87, 2019 | 4 | 2019 |
| A framework for asset prognostics from fleet data J Liu, E Zio 2016 prognostics and system health management conference (phm-chengdu), 1-5, 2016 | 4 | 2016 |
| Degradation state mining and identification for railway point machines C Bian, S Yang, T Huang, Q Xu, J Liu, E Zio Reliability Engineering & System Safety 188, 432-443, 2019 | 3 | 2019 |
| Ensemble of models for fatigue crack growth prognostics HP Nguyen, J Liu, E Zio IEEE Access 7, 49527-49537, 2019 | 3 | 2019 |
| A Data-Driven approach for predicting the remaining useful life of steam generators HP Nguyen, W Fauriat, E Zio, J Liu 2018 3rd International Conference on System Reliability and Safety (ICSRS …, 2018 | 2 | 2018 |
| Degradation detection method for railway point machines C Bian, S Yang, T Huang, Q Xu, J Liu, E Zio arXiv preprint arXiv:1809.02349, 2018 | 2 | 2018 |
Enrico ZioPolitecnico di Milano, CentralesupelecVerifisert e-postadresse på polimi.it
