Semantic Scholar Open Access 2024 44 sitasi

Enhanced soft Monte Carlo simulation coupled with SVR for structural reliability analysis

S. Yang Debiao Meng Hengfei Yang C. Luo Xiaoyan Su

Abstrak

In structural reliability analysis, it is a major challenge to develop a general method that can ensure high computational accuracy and low computational cost for low failure probability and high-dimensional problems. In this study, a novel enhanced simulation method named as enhanced Soft Monte Carlo Simulation coupled with Support Vector Regression (EMCS-SVR) is proposed. Firstly, a generalized Enhanced Simulation (ES) scaling formula is proposed as an improved scheme. Furthermore, the soft Monte Carlo simulation is combined with generalized ES scaling formula and support vector regression model for evaluating the failure probability. The efficiency and accuracy of the ESMCS-SVR are verified by comparing with existing popular method in four numerical examples and three engineering examples.

Penulis (5)

S. Yang

Debiao Meng

Hengfei Yang

C. Luo

Xiaoyan Su

Format Sitasi

APA MLA BibTeX

Yang, S., Meng, D., Yang, H., Luo, C., Su, X. (2024). Enhanced soft Monte Carlo simulation coupled with SVR for structural reliability analysis. https://doi.org/10.1680/jtran.24.00128

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Total Sitasi: 44×
Sumber Database: Semantic Scholar
DOI: 10.1680/jtran.24.00128
Akses: Open Access ✓