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Taotao Zhou, Te
Han, Enrique Lopez Droguett, Towards trustworthy machine fault diagnosis: A
probabilistic Bayesian deep learning framework, Reliability Engineering &
System Safety, Volume 224, 2022, 108525, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108525.
(https://www.sciencedirect.com/science/article/pii/S095183202200179X)
Michele Compare,
Federico Antonello, Luca Pinciroli, Enrico Zio, A general model for life-cycle
cost analysis of Condition-Based Maintenance enabled by PHM capabilities, Reliability
Engineering & System Safety, Volume 224, 2022, 108499, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108499.
(https://www.sciencedirect.com/science/article/pii/S0951832022001600)
Weiyi Chen, Limao
Zhang, An automated machine learning approach for earthquake casualty rate and
economic loss prediction, Reliability Engineering & System Safety, Volume
225, 2022, 108645, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108645.
(https://www.sciencedirect.com/science/article/pii/S0951832022002812)
Mingyang Zhang,
Pentti Kujala, Spyros Hirdaris, A machine learning method for the evaluation of
ship grounding risk in real operational conditions, Reliability Engineering
& System Safety, Volume 226, 2022, 108697, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108697.
(https://www.sciencedirect.com/science/article/pii/S0951832022003222)
Parth Bansal,
Zhuoyuan Zheng, Chenhui Shao, Jingjing Li, Mihaela Banu, Blair E Carlson,
Yumeng Li, Physics-informed machine learning assisted uncertainty
quantification for the corrosion of dissimilar material joints, Reliability
Engineering & System Safety, Volume 227, 2022, 108711, ISSN 0951-8320,
https://doi.org/10.1016/j.ress.2022.108711.
(https://www.sciencedirect.com/science/article/pii/S0951832022003362)
Jinwon Lee,
Changmo Yeo, Hyotae Kim, Duhwan Mun, Deep learning-based digitalization of a
part catalog book to generate part specification by a neutral reference data
dictionary, Computers in Industry, Volume 139, 2022, 103665, ISSN 0166-3615,
https://doi.org/10.1016/j.compind.2022.103665.
(https://www.sciencedirect.com/science/article/pii/S0166361522000628)
Ruoxin Wang, Chi
Fai Cheung, Chunjin Wang, Mei Na Cheng, Deep learning characterization of
surface defects in the selective laser melting process, Computers in Industry, Volume
140, 2022, 103662, ISSN 0166-3615,
https://doi.org/10.1016/j.compind.2022.103662.
(https://www.sciencedirect.com/science/article/pii/S0166361522000598)
Young-Hwan Choi, Jeongsam Yang, Machine learning iterative filtering
algorithm for field defect detection in the process stage, Computers in
Industry, Volume 142, 2022, 103740, ISSN 0166-3615,
https://doi.org/10.1016/j.compind.2022.103740.
(https://www.sciencedirect.com/science/article/pii/S0166361522001373)
Steven Malley,
Crystal Reina, Somer Nacy, Jérôme Gilles, Behrad Koohbor, George Youssef, Predictability
of mechanical behavior of additively manufactured particulate composites using
machine learning and data-driven approaches, Computers in Industry, Volume 142,
2022, 103739, ISSN 0166-3615,
https://doi.org/10.1016/j.compind.2022.103739.
(https://www.sciencedirect.com/science/article/pii/S0166361522001361)
Nan Xu, Zepeng
Tang, Hassan Askari, Jianfeng Zhou, Amir Khajepour, Direct tire slip ratio
estimation using intelligent tire system and machine learning algorithms, Mechanical
Systems and Signal Processing, Volume 175, 2022, 109085, ISSN 0888-3270,
https://doi.org/10.1016/j.ymssp.2022.109085.
(https://www.sciencedirect.com/science/article/pii/S0888327022002539)
Junchuan Shi,
Alexis Rivera, Dazhong Wu, Battery health management using physics-informed
machine learning: Online degradation modeling and remaining useful life
prediction, Mechanical Systems and Signal Processing, Volume 179, 2022, 109347,
ISSN 0888-3270,
https://doi.org/10.1016/j.ymssp.2022.109347.
(https://www.sciencedirect.com/science/article/pii/S0888327022004824)
Mingqiang Lin, Chenhao Yan, Jinhao Meng, Wei Wang, Ji Wu, Lithium-ion
batteries health prognosis via differential thermal capacity with simulated
annealing and support vector regression, Energy, Volume
250, 2022, 123829, ISSN 0360-5442,
https://doi.org/10.1016/j.energy.2022.123829.
(https://www.sciencedirect.com/science/article/pii/S0360544222007320)
Dengji Zhou,
Xingyun Jia, Shixi Ma, Tiemin Shao, Dawen Huang, Jiarui Hao, Taotao Li, Dynamic
simulation of natural gas pipeline network based on interpretable machine
learning model, Energy, Volume 253, 2022, 124068, ISSN 0360-5442,
https://doi.org/10.1016/j.energy.2022.124068.
(https://www.sciencedirect.com/science/article/pii/S0360544222009719)
Chu Zhang, Huixin
Ma, Lei Hua, Wei Sun, Muhammad Shahzad Nazir, Tian Peng, An evolutionary deep
learning model based on TVFEMD, improved sine cosine algorithm, CNN and BiLSTM
for wind speed prediction, Energy, Volume 254, Part A, 2022, 124250, ISSN
0360-5442,
https://doi.org/10.1016/j.energy.2022.124250.
(https://www.sciencedirect.com/science/article/pii/S0360544222011537)
Hang Zhang,
Shusheng Zhang, Yajun Zhang, Jiachen Liang, Zhen Wang, Machining feature recognition
based on a novel multi-task deep learning network, Robotics and
Computer-Integrated Manufacturing, Volume 77, 2022, 102369, ISSN 0736-5845,
https://doi.org/10.1016/j.rcim.2022.102369.
(https://www.sciencedirect.com/science/article/pii/S0736584522000564)
Jian Duan, Cheng
Hu, Xiaobin Zhan, Hongdi Zhou, Guanglan Liao, Tielin Shi, MS-SSPCANet: A
powerful deep learning framework for tool wear prediction, Robotics and Computer-Integrated
Manufacturing, Volume 78, 2022, 102391, ISSN 0736-5845,
https://doi.org/10.1016/j.rcim.2022.102391.
(https://www.sciencedirect.com/science/article/pii/S0736584522000783) |
