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| SVM based on response surface method for structural reliability analysis |
| Received:November 30, 2005 Revised:September 25, 2006 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20076141 |
| KeyWord:SVM,RSM,structural reliability analysis |
| JIN Wei-liang TANG Chun-xi CHEN Jin |
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| Abstract: |
| Implicit performance functions are normally encountered in structural reliability analysis while the structural systems are complicated.Response surface method(RSM) is very good at copping with the issue with implicit performance functions for its satisfied accuracy and good efficiency.The key point of RSM is the reconstruction of the response surface.However,the amount of sample set used to reconstruct the response surface is small.According to the excellent learning ability and generalization of support vector machine(SVM) even with small samples,the response surface of structure is reconstructed by SVM,and then a new RSM for structural reliability analysis was proposed on SVM.The present results compared well with those calculated by the conventional quadratic polynomial method and artificial neural network method.Furthermore,an improved RSM is developed by SVM,which can get a new response surface and a new design point by adding the old design point to sample set in iterative process.So no any results of FEM calculation is abnegated and the amount of FEM calculations is reduced dramatically.It is proved by examples that the calculation efficiencies and accuracy can be increased by proposed methods. |
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