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Support vector regression based metamodel by sequential adaptive sampling for reliability analysis of structures

Citations

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Cited by:

  1. Roy, Atin & Chakraborty, Subrata, 2022. "Reliability analysis of structures by a three-stage sequential sampling based adaptive support vector regression model," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  2. 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).
  3. Pepper, Nick & Crespo, Luis & Montomoli, Francesco, 2022. "Adaptive learning for reliability analysis using Support Vector Machines," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
  4. Wang, Run-Zi & Gu, Hang-Hang & Liu, Yu & Miura, Hideo & Zhang, Xian-Cheng & Tu, Shan-Tung, 2023. "Surrogate-modeling-assisted creep-fatigue reliability assessment in a low-pressure turbine disc considering multi-source uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
  5. Luo, Changqi & Zhu, Shun-Peng & Keshtegar, Behrooz & Niu, Xiaopeng & Taylan, Osman, 2023. "An enhanced uniform simulation approach coupled with SVR for efficient structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
  6. Xiao, Ning-Cong & Yuan, Kai & Zhan, Hongyou, 2022. "System reliability analysis based on dependent Kriging predictions and parallel learning strategy," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
  7. Lima, João P.S. & Evangelista, F. & Guedes Soares, C., 2023. "Hyperparameter-optimized multi-fidelity deep neural network model associated with subset simulation for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
  8. Bakeer, Tammam, 2023. "General partial safety factor theory for the assessment of the reliability of nonlinear structural systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
  9. 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).
  10. 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).
  11. Yuan, Kai & Sui, Xi & Zhang, Shijie & Xiao, Ning-cong & Hu, Jinghan, 2024. "AK-SYS-IE: A novel adaptive Kriging-based method for system reliability assessment combining information entropy," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
  12. Zhou, Tong & Peng, Yongbo, 2022. "Ensemble of metamodels-assisted probability density evolution method for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
  13. Zhou, Jin & Li, Jie, 2022. "An enhanced method for improving the accuracy of small failure probability of structures," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
  14. 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).
  15. Bi, Wenzhe & Tian, Li & Li, Chao & Ma, Zhen, 2023. "A Kriging-based probabilistic framework for multi-hazard performance assessment of transmission tower-line systems under coupled wind and rain loads," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
  16. Modibbo, Umar Muhammad & Arshad, Mohd. & Abdalghani, Omer & Ali, Irfan, 2021. "Optimization and estimation in system reliability allocation problem," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
  17. 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).
  18. Rujia Nie & Jinxing Che & Fang Yuan & Weihua Zhao, 2024. "Forecasting peak electric load: Robust support vector regression with smooth nonconvex ϵ‐insensitive loss," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1902-1917, September.
  19. Haoyuan, Shen & Yizhong, Ma & Chenglong, Lin & Jian, Zhou & Lijun, Liu, 2023. "Hierarchical Bayesian support vector regression with model parameter calibration for reliability modeling and prediction," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
  20. Roy, Atin & Chakraborty, Subrata, 2023. "Support vector machine in structural reliability analysis: A review," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
  21. Yu, Shui & Ren, Yuyao & Wu, Xiao & Guo, Peng & Li, Yun, 2024. "Dynamic pruning-based Bayesian support vector regression for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
  22. 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).
  23. Meng, Zeng & Zhao, Jingyu & Chen, Guohai & Yang, Dixiong, 2022. "Hybrid uncertainty propagation and reliability analysis using direct probability integral method and exponential convex model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
  24. Zhou, Tong & Peng, Yongbo, 2022. "Reliability analysis using adaptive Polynomial-Chaos Kriging and probability density evolution method," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
  25. 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).
  26. 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).
  27. Zhu, Chun-Yan & Li, Zhen-Ao & Dong, Xiao-Wei & Wang, Ming & Li, Qing-Da, 2024. "Collaborative modeling-based improved moving Kriging approach for low-cycle fatigue life reliability estimation of mechanical structures," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
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