Personal profile
Author IDs
ORCID iD: 0000-0002-1933-9886
Scopus Author ID: 57206657585
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Dive into the research topics where Ping ZHANG is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Research output
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A Joint Long Short-Term Memory and AdaBoost regression approach with application to remaining useful life estimation
Zhu, X., Zhang, P. & Xie, M., Jan 2021, In: Measurement. 170, 108707.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
50 Link opens in a new tab Citations (Scopus) -
A model-based reinforcement learning approach for maintenance optimization of degrading systems in a large state space
Zhang, P., Zhu, X. & Xie, M., Nov 2021, In: Computers and Industrial Engineering. 161, 107622.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
46 Link opens in a new tab Citations (Scopus) -
Exploiting structural similarity in network reliability analysis using graph learning
Zhang, P., Xie, M. & Zhu, X., 1 Dec 2021, In: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. 235, 6, p. 1057-1071Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
2 Link opens in a new tab Citations (Scopus) -
Spectral Graph Wavelet based Component Clustering for System Reliability Analysis
Zhang, P. & Zhu, X., Dec 2018, 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018. IEEE, p. 1135-1139 8607637. (IEEE International Conference on Industrial Engineering and Engineering Management; vol. 2019-December).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
1 Link opens in a new tab Citation (Scopus)
Thesis
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ZHANG, P. (Author), Zhu, X. (External Supervisor) & XIE, M. (Supervisor), 3 Aug 2021Data-driven Methods for System Reliability Analysis and Maintenance Optimization
Student thesis: Doctoral Thesis