Gaussian process regression for numerical wind speed prediction enhancement H Cai, X Jia, J Feng, W Li, YM Hsu, J Lee Renewable energy 146, 2112-2123, 2020 | 155 | 2020 |
Intelligent maintenance systems and predictive manufacturing J Lee, J Ni, J Singh, B Jiang, M Azamfar, J Feng Journal of Manufacturing Science and Engineering 142 (11), 110805, 2020 | 131 | 2020 |
Prognosability study of ball screw degradation using systematic methodology P Li, X Jia, J Feng, H Davari, G Qiao, Y Hwang, J Lee Mechanical Systems and Signal Processing 109, 45-57, 2018 | 101 | 2018 |
Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks X Jia, Y Di, J Feng, Q Yang, H Dai, J Lee Journal of Process Control 62, 44-54, 2018 | 88 | 2018 |
A review of PHM Data Competitions from 2008 to 2017: Methodologies and Analytics X Jia, B Huang, J Feng, H Cai, J Lee Proceedings of the Annual Conference of the Prognostics and Health …, 2018 | 61 | 2018 |
Similarity-based particle filter for remaining useful life prediction with enhanced performance H Cai, J Feng, W Li, YM Hsu, J Lee Applied Soft Computing 94, 106474, 2020 | 60 | 2020 |
A combined filtering strategy for short term and long term wind speed prediction with improved accuracy H Cai, X Jia, J Feng, Q Yang, YM Hsu, Y Chen, J Lee Renewable energy 136, 1082-1090, 2019 | 50 | 2019 |
A similarity based methodology for machine prognostics by using kernel two sample test H Cai, X Jia, J Feng, W Li, L Pahren, J Lee ISA transactions 103, 112-121, 2020 | 46 | 2020 |
A virtual metrology method with prediction uncertainty based on Gaussian process for chemical mechanical planarization H Cai, J Feng, Q Yang, W Li, X Li, J Lee Computers in Industry 119, 103228, 2020 | 40 | 2020 |
Performance degradation assessment of wind turbine gearbox based on maximum mean discrepancy and multi-sensor transfer learning Y Pan, R Hong, J Chen, J Feng, W Wu Structural Health Monitoring 20 (1), 118-138, 2021 | 35 | 2021 |
A novel scalable method for machine degradation assessment using deep convolutional neural network P Li, X Jia, J Feng, F Zhu, M Miller, LY Chen, J Lee Measurement 151, 107106, 2020 | 32 | 2020 |
Evaluating feature selection and anomaly detection methods of hard drive failure prediction Q Yang, X Jia, X Li, J Feng, W Li, J Lee IEEE Transactions on Reliability 70 (2), 749-760, 2020 | 31 | 2020 |
An Online Virtual Metrology Model with Sample Selection for the Tracking of Dynamic Manufacturing Processes with Slow Drift J Feng, X Jia, F Zhu, J Moyne, J Iskandar, J Lee IEEE Transactions on Semiconductor Manufacturing, 1-1, 2019 | 28 | 2019 |
Adaptive virtual metrology method based on Just-in-time reference and particle filter for semiconductor manufacturing H Cai, J Feng, F Zhu, Q Yang, X Li, J Lee Measurement 168, 108338, 2021 | 20 | 2021 |
Cross trajectory gaussian process regression model for battery health prediction J Feng, X Jia, H Cai, F Zhu, X Li, J Lee Journal of modern power systems and clean energy 9 (5), 1217-1226, 2020 | 16 | 2020 |
An intelligent system for off-shore wind farm maintenance scheduling optimization considering turbine production loss J Feng, X Jia, F Zhu, Q Yang, Y Pan, J Lee Journal of Intelligent & Fuzzy Systems, 1-13, 2019 | 16 | 2019 |
A novel similarity-based method for remaining useful life prediction using kernel two sample test X Jia, H Cai, Y Hsu, W Li, J Feng, J Lee Proceedings of the Annual Conference of the PHM Society 11, 2019 | 15 | 2019 |
A unified Bayesian filtering framework for multi-horizon wind speed prediction with improved accuracy H Cai, X Jia, J Feng, Q Yang, W Li, F Li, J Lee Renewable Energy 178, 709-719, 2021 | 12 | 2021 |
A framework for semi-automated fault detection configuration with automated feature extraction and limits setting H Cai, J Feng, J Moyne, J Iskandar, M Armacost, F Li, J Lee 2020 31st Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC …, 2020 | 8 | 2020 |
Modeling and solution of offshore wind farm maintenance scheduling HZ Tan, W Lv, LW Jin, ZC Liu, JS Feng DEStech Trans. Environ. Energy Earth Sci, 2017 | 7 | 2017 |