支持向量机
脆弱性
可靠性(半导体)
云计算
结构工程
计算机科学
数据挖掘
工程类
核(代数)
可靠性工程
机器学习
数学
功率(物理)
化学
物理
物理化学
量子力学
组合数学
操作系统
作者
Benbo Sun,Mingjiang Deng,Sherong Zhang,Weiying Liu,Jia Xu,Wang Cha,Wei Cui
标识
DOI:10.1080/13632469.2023.2300487
摘要
One of the primary concerns in the field of seismic risk assessment for underground structures is establishing an accurate connection between seismic intensity and structural responses. The objective of this work is to conduct a rational support vector machine (SVM) model for generating mass data and improved fragility curves of cross-fault hydraulic tunnels (CFHTs). The results highlight that the 900 sets, multiple earthquake intensity measures, and cubic polynomial kernel function of the SVM model can improve reliability in evaluating structural performance. Additionally, the improved Cloud analysis method is more suitable for seismic performance than the typical Cloud analysis.
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