LIF: A new Kriging based learning function and its application to structural reliability analysis

Citations

Cited by:

1. Cui, Da & Wang, Guoqiang & Lu, Yanpeng & Sun, Kangkang, 2020. "Reliability design and optimization of the planetary gear by a GA based on the DEM and Kriging model," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
2. Jian, Wang & Zhili, Sun & Qiang, Yang & Rui, Li, 2017. "Two accuracy measures of the Kriging model for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 494-505.
3. Xiao, Ning-Cong & Zuo, Ming J. & Zhou, Chengning, 2018. "A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 330-338.
4. Li, Mingyang & Wang, Zequn, 2019. "Surrogate model uncertainty quantification for reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
5. Wu, Xu & Kozlowski, Tomasz & Meidani, Hadi, 2018. "Kriging-based inverse uncertainty quantification of nuclear fuel performance code BISON fission gas release model using time series measurement data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 422-436.
6. Wang, Dapeng & Qiu, Haobo & Gao, Liang & Jiang, Chen, 2024. "A Subdomain uncertainty-guided Kriging method with optimized feasibility metric for time-dependent reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
7. Wei, Pengfei & Zheng, Yu & Fu, Jiangfeng & Xu, Yuannan & Gao, Weikai, 2023. "An expected integrated error reduction function for accelerating Bayesian active learning of failure probability," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
8. Chengning Zhou & Caixue Liu & Taibo Yang & Pan He & Cuiyun Peng & Na Zhe, 2023. "An adaptive Kriging-based structural reliability analysis method combing dichotomy and improved convergence criterion," Journal of Risk and Reliability, , vol. 237(6), pages 1114-1131, December.
9. Keshtegar, Behrooz & Kisi, Ozgur, 2018. "RM5Tree: Radial basis M5 model tree for accurate structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 49-61.
10. Xin, Fukang & Wang, Pan & Wang, Qirui & Li, Lei & Cheng, Lei & Lei, Huajin & Ma, Fangyun, 2024. "Parallel adaptive ensemble of metamodels combined with hypersphere sampling for rare failure events," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
11. Cheng, Kai & Lu, Zhenzhou, 2021. "Adaptive Bayesian support vector regression model for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
12. Wang, Jian & Sun, Zhili & Cao, Runan, 2021. "An efficient and robust Kriging-based method for system reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
13. Ma, Yuan-Zhuo & Zhu, Yi-Chen & Li, Hong-Shuang & Nan, Hang & Zhao, Zhen-Zhou & Jin, Xiang-Xiang, 2022. "Adaptive Kriging-based failure probability estimation for multiple responses," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
14. Feng, Kaixuan & Lu, Zhenzhou & Yang, Yixin & Ling, Chunyan & He, Pengfei & Dai, Ying, 2023. "Novel Kriging based learning function for system reliability analysis with correlated failure modes," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
15. Zhu, Xianming & Lu, Zhenzhou & Yun, Wanying, 2020. "An efficient method for estimating failure probability of the structure with multiple implicit failure domains by combining Meta-IS with IS-AK," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
16. Jingkui Li & Wenqi Liu & Yan Zhou & Zhandong Li, 2023. "An active learning Kriging-based method combining the weight information entropy function and the adaptive candidate sample pool," Journal of Risk and Reliability, , vol. 237(4), pages 741-751, August.
17. Chen, Zequan & Li, Guofa & He, Jialong & Yang, Zhaojun & Wang, Jili, 2022. "Adaptive structural reliability analysis method based on confidence interval squeezing," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
18. Zhang, Jinhao & Xiao, Mi & Gao, Liang, 2019. "An active learning reliability method combining Kriging constructed with exploration and exploitation of failure region and subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 90-102.
19. Hongxiang Zhao & Wei Shao & Zheng Cui & Chen Zheng, 2023. "Multi-Objective Parameter Optimization of Pulse Tube Refrigerator Based on Kriging Metamodel and Non-Dominated Ranking Genetic Algorithms," Energies, MDPI, vol. 16(6), pages 1-18, March.
20. Dang, Chao & Wei, Pengfei & Faes, Matthias G.R. & Valdebenito, Marcos A. & Beer, Michael, 2022. "Parallel adaptive Bayesian quadrature for rare event estimation," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
21. Ni, Pinghe & Li, Jun & Hao, Hong & Yan, Weimin & Du, Xiuli & Zhou, Hongyuan, 2020. "Reliability analysis and design optimization of nonlinear structures," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
22. Wang, Jinsheng & Xu, Guoji & Yuan, Peng & Li, Yongle & Kareem, Ahsan, 2024. "An efficient and versatile Kriging-based active learning method for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
23. Xu, Jun & Wang, Ding, 2019. "Structural reliability analysis based on polynomial chaos, Voronoi cells and dimension reduction technique," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 329-340.
24. Chengning Zhou & Ning-Cong Xiao & Ming J Zuo & Xiaoxu Huang, 2020. "AK-PDF: An active learning method combining kriging and probability density function for efficient reliability analysis," Journal of Risk and Reliability, , vol. 234(3), pages 536-549, June.
25. Zhang, Chi & Shafieezadeh, Abdollah, 2022. "Simulation-free reliability analysis with active learning and Physics-Informed Neural Network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
26. Bolin Liu & Liyang Xie, 2020. "An Improved Structural Reliability Analysis Method Based on Local Approximation and Parallelization," Mathematics, MDPI, vol. 8(2), pages 1-13, February.
27. Yu, Ting & Lu, Zhenzhou & Yun, Wanying, 2023. "An efficient algorithm for analyzing multimode structure system reliability by a new learning function of most reducing average probability of misjudging system state," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
28. Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
29. Li, Junxiang & Chen, Jianqiao, 2019. "Solving time-variant reliability-based design optimization by PSO-t-IRS: A methodology incorporating a particle swarm optimization algorithm and an enhanced instantaneous response surface," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
30. Zhang, Yu & Dong, You & Frangopol, Dan M., 2024. "An error-based stopping criterion for spherical decomposition-based adaptive Kriging model and rare event estimation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
31. Zhou, Jin & Li, Jie, 2023. "IE-AK: A novel adaptive sampling strategy based on information entropy for Kriging in metamodel-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
32. Yang, Xufeng & Liu, Yongshou & Mi, Caiying & Tang, Chenghu, 2018. "System reliability analysis through active learning Kriging model with truncated candidate region," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 235-241.
33. Cheng, Kai & Lu, Zhenzhou, 2019. "Time-variant reliability analysis based on high dimensional model representation," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 310-319.
34. Zuhal, Lavi Rizki & Faza, Ghifari Adam & Palar, Pramudita Satria & Liem, Rhea Patricia, 2021. "On dimensionality reduction via partial least squares for Kriging-based reliability analysis with active learning," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
35. Okoro, Aghatise & Khan, Faisal & Ahmed, Salim, 2023. "Dependency effect on the reliability-based design optimization of complex offshore structure," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
36. Guo, Qing & Liu, Yongshou & Chen, Bingqian & Yao, Qin, 2021. "A variable and mode sensitivity analysis method for structural system using a novel active learning Kriging model," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
37. Dong, Y. & Teixeira, A.P. & Guedes Soares, C., 2020. "Application of adaptive surrogate models in time-variant fatigue reliability assessment of welded joints with surface cracks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
38. Chen, Zequan & He, Jialong & Li, Guofa & Yang, Zhaojun & Wang, Tianzhe & Du, Xuejiao, 2024. "Fast convergence strategy for adaptive structural reliability analysis based on kriging believer criterion and importance sampling," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
39. Wang, Zeyu & Shafieezadeh, Abdollah, 2020. "On confidence intervals for failure probability estimates in Kriging-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
40. Zhang, Jinhao & Gao, Liang & Xiao, Mi, 2020. "A composite-projection-outline-based approximation method for system reliability analysis with hybrid uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
41. Li, Wenxiong & Geng, Rong & Chen, Suiyin, 2024. "CSP-free adaptive Kriging surrogate model method for reliability analysis with small failure probability," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
42. Qin, Zhiyuan & Naser, M.Z., 2023. "Machine learning and model driven bayesian uncertainty quantification in suspended nonstructural systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
43. Chen, Weidong & Xu, Chunlong & Shi, Yaqin & Ma, Jingxin & Lu, Shengzhuo, 2019. "A hybrid Kriging-based reliability method for small failure probabilities," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 31-41.
44. Chen, Zequan & Li, Guofa & He, Jialong & Yang, Zhaojun & Wang, Jili, 2022. "A new parallel adaptive structural reliability analysis method based on importance sampling and K-medoids clustering," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
45. Wang, Zeyu & Shafieezadeh, Abdollah, 2020. "Real-time high-fidelity reliability updating with equality information using adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
46. Chen, Jiahui & Chen, Zhicheng & Xu, Yang & Li, Hui, 2021. "Efficient reliability analysis combining kriging and subset simulation with two-stage convergence criterion," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
47. Teixeira, Rui & Nogal, Maria & O’Connor, Alan & Martinez-Pastor, Beatriz, 2020. "Reliability assessment with density scanned adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
48. Jakeman, John D. & Kouri, Drew P. & Huerta, J. Gabriel, 2022. "Surrogate modeling for efficiently, accurately and conservatively estimating measures of risk," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
49. Jing, Zhao & Chen, Jianqiao & Li, Xu, 2019. "RBF-GA: An adaptive radial basis function metamodeling with genetic algorithm for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 42-57.
50. Shi, Yan & Lu, Zhenzhou & He, Ruyang & Zhou, Yicheng & Chen, Siyu, 2020. "A novel learning function based on Kriging for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
51. Song, Kunling & Zhang, Yugang & Shen, Linjie & Zhao, Qingyan & Song, Bifeng, 2021. "A failure boundary exploration and exploitation framework combining adaptive Kriging model and sample space partitioning strategy for efficient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
52. Jiang, Chen & Qiu, Haobo & Yang, Zan & Chen, Liming & Gao, Liang & Li, Peigen, 2019. "A general failure-pursuing sampling framework for surrogate-based reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 47-59.
53. Wang, Zeyu & Shafieezadeh, Abdollah, 2019. "REAK: Reliability analysis through Error rate-based Adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 33-45.
54. Yang, Seonghyeok & Jo, Hwisang & Lee, Kyungeun & Lee, Ikjin, 2022. "Expected system improvement (ESI): A new learning function for system reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
55. Zhang, Yu & Dong, You & Xu, Jun, 2023. "An accelerated active learning Kriging model with the distance-based subdomain and a new stopping criterion for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
56. Keshtegar, Behrooz & Chakraborty, Subrata, 2018. "An efficient-robust structural reliability method by adaptive finite-step length based on Armijo line search," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 195-206.
57. Zuniga, M. Munoz & Murangira, A. & Perdrizet, T., 2021. "Structural reliability assessment through surrogate based importance sampling with dimension reduction," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
58. Wang, Lei & Hu, Zhuo & Dang, Chao & Beer, Michael, 2024. "Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
59. 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).
60. Teixeira, Rui & Martinez-Pastor, Beatriz & Nogal, Maria & O’Connor, Alan, 2021. "Reliability analysis using a multi-metamodel complement-basis approach," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
61. Di Maio, F. & Belotti, M. & Volpe, M. & Selva, J. & Zio, E., 2022. "Parallel density scanned adaptive Kriging to improve local tsunami hazard assessment for coastal infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
62. Ameryan, Ala & Ghalehnovi, Mansour & Rashki, Mohsen, 2022. "AK-SESC: a novel reliability procedure based on the integration of active learning kriging and sequential space conversion method," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
63. Wei, Pengfei & Liu, Fuchao & Tang, Chenghu, 2018. "Reliability and reliability-based importance analysis of structural systems using multiple response Gaussian process model," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 183-195.
64. Xiao, Sinan & Oladyshkin, Sergey & Nowak, Wolfgang, 2020. "Reliability analysis with stratified importance sampling based on adaptive Kriging," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
65. Jiang, Chen & Qiu, Haobo & Gao, Liang & Wang, Dapeng & Yang, Zan & Chen, Liming, 2020. "EEK-SYS: System reliability analysis through estimation error-guided adaptive Kriging approximation of multiple limit state surfaces," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
66. Zhang, Xufang & Wang, Lei & Sørensen, John Dalsgaard, 2019. "REIF: A novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 440-454.
67. Wang, Run-Zi & Gu, Hang-Hang & Zhu, Shun-Peng & Li, Kai-Shang & Wang, Ji & Wang, Xiao-Wei & Hideo, Miura & Zhang, Xian-Cheng & Tu, Shan-Tung, 2022. "A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
68. Yi, Jiaxiang & Cheng, Yuansheng & Liu, Jun, 2022. "A novel fidelity selection strategy-guided multifidelity kriging algorithm for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
69. Li, Peiping & Wang, Yu, 2022. "An active learning reliability analysis method using adaptive Bayesian compressive sensing and Monte Carlo simulation (ABCS-MCS)," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
70. Xu, Jun & Kong, Fan, 2018. "A new unequal-weighted sampling method for efficient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 94-102.
71. Xiao, Mi & Zhang, Jinhao & Gao, Liang, 2020. "A system active learning Kriging method for system reliability-based design optimization with a multiple response model," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
72. Wang, Jinsheng & Xu, Guoji & Li, Yongle & Kareem, Ahsan, 2022. "AKSE: A novel adaptive Kriging method combining sampling region scheme and error-based stopping criterion for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
73. 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).
74. Du, Weiqi & Luo, Yuanxin & Wang, Yongqin, 2019. "Time-variant reliability analysis using the parallel subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 250-257.
75. Yang, Seonghyeok & Lee, Mingyu & Lee, Ikjin, 2023. "A new sampling approach for system reliability-based design optimization under multiple simulation models," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
76. 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).
77. Xiong, Yifang & Sampath, Suresh, 2021. "A fast-convergence algorithm for reliability analysis based on the AK-MCS," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
78. Castellon, Dario Fernandez & Fenerci, Aksel & Petersen, Øyvind Wiig & Øiseth, Ole, 2023. "Full long-term buffeting analysis of suspension bridges using Gaussian process surrogate modelling and importance sampling Monte Carlo simulations," Reliability Engineering and System Safety, Elsevier, vol. 235(C).