@inproceedings{0f0bb82a8c04405085c501814607e753,
title = "Application of IWO-SVM approach in fault diagnosis of analog circuits",
abstract = "Support vector machine (SVM) is a machine learning algorithm which has been applied to fault diagnosis of analog circuits. Invasive weed optimization (IWO) is a novel numerical optimization algorithm inspired from weed colonization. An approach that combines IWO and SVM (IWO-SVM) is proposed to fault diagnosis of analog circuits in this paper. The process of fault diagnosis of analog circuits using IWO-SVM approach is introduced in details. A biquadrate filter is used to test the performance of IWO-SVM approach for fault diagnosis. The simulation experiments show that the IWO-SVM approach proposed in this paper has a higher diagnosis accuracy rate than the conventional SVM in fault diagnosis of analog circuits.",
keywords = "Analog Circuits, Fault Diagnosis, IWO, IWO-SVM, SVM",
author = "Shuxiang Cai and Haiwen Yuan and Jianxun Lv and Yang Cui",
year = "2013",
doi = "10.1109/CCDC.2013.6561800",
language = "英语",
isbn = "9781467355322",
series = "2013 25th Chinese Control and Decision Conference, CCDC 2013",
pages = "4786--4791",
booktitle = "2013 25th Chinese Control and Decision Conference, CCDC 2013",
note = "2013 25th Chinese Control and Decision Conference, CCDC 2013 ; Conference date: 25-05-2013 Through 27-05-2013",
}