@inproceedings{1ef5d436438045bcbc6d03192353e7c2,
title = "Research on Response Surface Method of Support Vector Machine based on Markov Chain",
abstract = "The common form of response surface methods affect the accuracy of reliability calculation in the experimental design because of the over dependence on the selection of experimental points. Based on the characteristics of the Least Square Support Vector Machine (LSSVM), a method to obtain the approximate designed points was designed by using an adaptive Markov Chain to simulate the samples in the failure domain and the safety domain. The improved selection method of design point could be used to select the samples adaptively at the real limit state boundary, to improve the fitting precision of the real boundary and increase the calculation precision of reliability. In this article, two cases of the multiple failure mode and the single failure mode with complex boundary are studied and compared to other methods to illustrate the advantages of the proposed method.",
keywords = "markov chain, reliability, response surface method, support vector machine",
author = "Jiadong Qiao and Sen Li and Tong Zhang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018 ; Conference date: 12-10-2018 Through 14-10-2018",
year = "2018",
month = dec,
day = "14",
doi = "10.1109/IAEAC.2018.8577509",
language = "English",
series = "Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2359--2364",
editor = "Bing Xu",
booktitle = "Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018",
address = "United States",
}