Jie Liu
Jie Liu
Associate Professor, Beihang University
Verifisert e-postadresse på buaa.edu.cn - Startside
TittelSitert avÅr
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
532013
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
312017
System dynamic reliability assessment and failure prognostics
J Liu, E Zio
Reliability Engineering & System Safety 160, 21-36, 2017
272017
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
252016
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
182015
A SVR-based ensemble approach for drifting data streams with recurring patterns
J Liu, E Zio
Applied Soft Computing 47, 553-564, 2016
92016
A scalable fuzzy support vector machine for fault detection in transportation systems
J Liu, E Zio
Expert Systems with Applications 102, 36-43, 2018
82018
Feature vector regression with efficient hyperparameters tuning and geometric interpretation
J Liu, E Zio
Neurocomputing 218, 411-422, 2016
72016
SVM hyperparameters tuning for recursive multi-step-ahead prediction
J Liu, E Zio
Neural Computing and Applications, 1-15, 2016
72016
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
62019
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
52016
Dynamic reliability assessment and prognostics with monitored data for multiple dependent degradation components
J Liu, E Zio
European Safety and Reliability Conference, 2016
52016
Dynamic weighted PSVR-based ensembles for prognostics of nuclear components
J Liu, V Vitelli, R Seraoui, E Zio
FLINS 2014, 2014
52014
Weighted-feature and cost-sensitive regression model for component continuous degradation assessment
J Liu, E Zio
Reliability Engineering & System Safety 168, 210-217, 2017
42017
A framework for asset prognostics from fleet data
J Liu, E Zio
2016 Prognostics and System Health Management Conference (PHM-Chengdu), 1-5, 2016
42016
Ensemble of Models for Fatigue Crack Growth Prognostics
HP Nguyen, J Liu, E Zio
IEEE Access 7, 49527-49537, 2019
22019
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
12019
Prognostics of a multistack PEMFC system with multiagent modeling
J Liu, E Zio
Energy Science & Engineering 7 (1), 76-87, 2019
12019
Particle filtering for prognostics of a newly designed product with a new parameters initialization strategy based on reliability test data
J Liu, E Zio, Y Hu
IEEE Access 6, 62564-62573, 2018
12018
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
12018
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Artikler 1–20