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| Stable fitting of complex failure functions and correct classifying of sample points based on multiple linear support vector machines |
| Received:May 07, 2014 Revised:August 01, 2014 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx201503004 |
| KeyWord:structural reliability support vector correct classifying sample pair uniform design failure function |
| Author | Institution |
| 蒋友宝 |
长沙理工大学 土木与建筑学院, 长沙 |
| 黄星星 |
长沙理工大学 土木与建筑学院, 长沙 |
| 廖国宇 |
长沙理工大学 土木与建筑学院, 长沙 |
| 张建仁 |
长沙理工大学 土木与建筑学院, 长沙 |
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| Abstract: |
| To overcome the shortcomings of the current response surface methods,which are less accurate and need a large number of samples to rebuild a complex implicit failure function,a new fitting method of structural failure function is proposed based on multiple linear support vector machines.One of the main features of this method is the application of correct classifying techniques of sample points.Thus,its solution can approximate the real failure function steadily as the number of samples increases.Its main solving steps are:(1) use the uniform design method to generate reliable and failure samples,which are close to the real limit state surface;(2) divide the total space into multiple subspaces based on vector modules and angles of sample points to ensure that the sample points in each space can be classified correctly by a linear support vector machine;(3) establish an iterative algorithm based on additional sample pairs to update sample sets continuously to modify the obtained multiple linear support vector machines.Numerical examples show that this method has a better accuracy and efficiency,no matter the failure function is a highly nonlinear one or a piecewise one due to its multiple failure modes.This method provides a useful basis for the reliability analysis of structure with a complex failure function. |