Deep adaptive arbitrary polynomial chaos expansion: A mini-data-driven semi-supervised method for uncertainty quantification
Author
Abstract
Suggested Citation
DOI: 10.1016/j.ress.2022.108813
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Kröker, Ilja & Oladyshkin, Sergey, 2022. "Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xiaoqian, 2020. "Algorithms for Bayesian network modeling and reliability inference of complex multistate systems: Part I – Independent systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
- El Moçayd, Nabil & Seaid, Mohammed, 2021. "Data-driven polynomial chaos expansions for characterization of complex fluid rheology: Case study of phosphate slurry," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
- Lee, Seunggyu, 2021. "Monte Carlo simulation using support vector machine and kernel density for failure probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
- Schöbi, Roland & Sudret, Bruno, 2019. "Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 129-141.
- Yang, Zhe & Baraldi, Piero & Zio, Enrico, 2022. "A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
- Cao, Quoc Dung & Miles, Scott B. & Choe, Youngjun, 2022. "Infrastructure recovery curve estimation using Gaussian process regression on expert elicited data," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
- Echard, B. & Gayton, N. & Lemaire, M. & Relun, N., 2013. "A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 232-240.
- Kapusuzoglu, Berkcan & Mahadevan, Sankaran, 2021. "Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
- Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xianqi, 2019. "Improved compression inference algorithm for reliability analysis of complex multistate satellite system based on multilevel Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 123-142.
- Ye, Dongwei & Nikishova, Anna & Veen, Lourens & Zun, Pavel & Hoekstra, Alfons G., 2021. "Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
- Zhang, Z. & Jiang, C. & Wang, G.G. & Han, X., 2015. "First and second order approximate reliability analysis methods using evidence theory," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 40-49.
- Mara, Thierry A. & Becker, William E., 2021. "Polynomial chaos expansion for sensitivity analysis of model output with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
- Xu, Danyang & Qiu, Haobo & Gao, Liang & Yang, Zan & Wang, Dapeng, 2022. "A novel dual-stream self-attention neural network for remaining useful life estimation of mechanical systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Pan, Qiujing & Dias, Daniel, 2017. "Sliced inverse regression-based sparse polynomial chaos expansions for reliability analysis in high dimensions," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 484-493.
- Palar, Pramudita Satria & Zuhal, Lavi Rizki & Shimoyama, Koji & Tsuchiya, Takeshi, 2018. "Global sensitivity analysis via multi-fidelity polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 175-190.
- Oladyshkin, Sergey & Nowak, Wolfgang, 2018. "Incomplete statistical information limits the utility of high-order polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 137-148.
- Papaioannou, Iason & Straub, Daniel, 2021. "Variance-based reliability sensitivity analysis and the FORM α-factors," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
- Ökten, Giray & Liu, Yaning, 2021. "Randomized quasi-Monte Carlo methods in global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
- Zhou, Yicheng & Lu, Zhenzhou & Yun, Wanying, 2020. "Active sparse polynomial chaos expansion for system reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
- Lim, HyeongUk & Manuel, Lance, 2021. "Distribution-free polynomial chaos expansion surrogate models for efficient structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
- Torii, André Jacomel & Novotny, Antonio André, 2021. "A priori error estimates for local reliability-based sensitivity analysis with Monte Carlo Simulation," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
- Oladyshkin, S. & Nowak, W., 2012. "Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 179-190.
- Razaaly, Nassim & Congedo, Pietro Marco, 2020. "Extension of AK-MCS for the efficient computation of very small failure probabilities," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
- Li, Meng & Sadoughi, Mohammadkazem & Hu, Zhen & Hu, Chao, 2020. "A hybrid Gaussian process model for system reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
- Bao, Yuequan & Xiang, Zhengliang & Li, Hui, 2021. "Adaptive subset searching-based deep neural network method for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
- Saraygord Afshari, Sajad & Enayatollahi, Fatemeh & Xu, Xiangyang & Liang, Xihui, 2022. "Machine learning-based methods in structural reliability analysis: A review," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Wu, Jinhui & Tao, Yourui & Han, Xu, 2023. "Polynomial chaos expansion approximation for dimension-reduction model-based reliability analysis method and application to industrial robots," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Wang, Ning, 2024. "Algorithms for Bayesian network modeling and reliability inference of complex multistate systems with common cause failure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
- Zheng, Xiaohu & Yao, Wen & Zhang, Xiaoya & Qian, Weiqi & Zhang, Hairui, 2023. "Parameterized coefficient fine-tuning-based polynomial chaos expansion method for sphere-biconic reentry vehicle reliability analysis and design," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
- Shih-Cheng Horng & Shieh-Shing Lin, 2023. "Improved Beluga Whale Optimization for Solving the Simulation Optimization Problems with Stochastic Constraints," Mathematics, MDPI, vol. 11(8), pages 1-17, April.
- Hong, Xu & Wan, Zhiqiang & Chen, Jianbing, 2023. "Parallel assessment of the tropical cyclone wind hazard at multiple locations using the probability density evolution method integrated with the change of probability measure," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
- Nan, Hang & Liang, Hao & Di, Haoyuan & Li, Hongshuang, 2024. "A gradient-assisted learning strategy of Kriging model for robust design optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
- Guan, Xuefei, 2024. "Sparse moment quadrature for uncertainty modeling and quantification," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Zheng, Xiaohu & Yao, Wen & Zhang, Yunyang & Zhang, Xiaoya, 2022. "Consistency regularization-based deep polynomial chaos neural network method for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
- Zheng, Xiaohu & Yao, Wen & Zhang, Xiaoya & Qian, Weiqi & Zhang, Hairui, 2023. "Parameterized coefficient fine-tuning-based polynomial chaos expansion method for sphere-biconic reentry vehicle reliability analysis and design," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
- Palar, Pramudita Satria & Zuhal, Lavi Rizki & Shimoyama, Koji, 2023. "Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
- Mathpati, Yogesh Chandrakant & More, Kalpesh Sanjay & Tripura, Tapas & Nayek, Rajdip & Chakraborty, Souvik, 2023. "MAntRA: A framework for model agnostic reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
- Kröker, Ilja & Oladyshkin, Sergey, 2022. "Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Jung, WoongHee & Taflanidis, Alexandros A., 2023. "Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
- Wang, Yanzhong & Xie, Bin & E, Shiyuan, 2022. "Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
- Li, Guosheng & Ma, Shuaichao & Zhang, Dequan & Yang, Leping & Zhang, Weihua & Wu, Zeping, 2024. "An efficient sequential anisotropic RBF reliability analysis method with fast cross-validation and parallelizability," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
- Guan, Xiaoshu & Sun, Huabin & Hou, Rongrong & Xu, Yang & Bao, Yuequan & Li, Hui, 2023. "A deep reinforcement learning method for structural dominant failure modes searching based on self-play strategy," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
- Chunyan, Ling & Jingzhe, Lei & Way, Kuo, 2022. "Bayesian support vector machine for optimal reliability design of modular systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
- Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
- Shang, Yue & Nogal, Maria & Teixeira, Rui & Wolfert, A.R. (Rogier) M., 2024. "Extreme-oriented sensitivity analysis using sparse polynomial chaos expansion. Application to train–track–bridge systems," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
- Chen, Xuyong & Xu, Zhifeng & Wu, Yushun & Wu, Qiaoyun, 2023. "Heuristic algorithms for reliability estimation based on breadth-first search of a grid tree," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
- Xu, Hui & Grigoriu, Mircea D. & Gurley, Kurtis R., 2023. "A novel surrogate for extremes of random functions," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
- Zhang, Qiang & Zhao, Yan-Gang & Kolozvari, Kristijan & Xu, Lei, 2022. "Reliability analysis of reinforced concrete structure against progressive collapse," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
- Wang, Zhenqiang & Jia, Gaofeng, 2023. "Extended sample-based approach for efficient sensitivity analysis of group of random variables," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
- Zhang, Jian & Gong, Weijie & Yue, Xinxin & Shi, Maolin & Chen, Lei, 2022. "Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
- Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
- Thapa, Mishal & Missoum, Samy, 2022. "Uncertainty quantification and global sensitivity analysis of composite wind turbine blades," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Wang, Zihan & Daeipour, Mohamad & Xu, Hongyi, 2023. "Quantification and propagation of Aleatoric uncertainties in topological structures," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
More about this item
Keywords
Mini-data; Arbitrary polynomial chaos expansion; Deep learning; Semi-supervised; Uncertainty quantification;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:229:y:2023:i:c:s095183202200432x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.