Structural Reliability Analysis Based on Support Vector Machine and Dual Neural Network Direct Integration Method

• 作者: NIE Xiaobo LI Haibin
• 来源期刊: 东华大学学报（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: Intelligent Detection and Control
• 页码范围: 51-56
• 页数: 6页
• 分类号: TH114
• 语种: 英文
• DOI: 10.19884/j.1672-5220.202009069

摘要

Aiming at the reliability analysis of small sample data or implicit structural function,a novel structural reliability analysis model based on support vector machine(SVM)and neural network direct integration method(DNN)is proposed.Firstly,SVM with good small sample learning ability is used to train small sample data,fit structural performance functions and establish regular integration regions.Secondly,DNN is approximated the integral function to achieve multiple integration in the integration region.Finally,structural reliability was obtained by DNN.Numerical examples are investigated to demonstrate the effectiveness of the present method,which provides a feasible way for the structural reliability analysis.