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Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine
Joint Authors
Ding, Mingli
Yang, Dongmei
Li, Xiaobing
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-24
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Various data mining techniques have been applied to fault diagnosis for wireless sensor because of the advantage of discovering useful knowledge from large data sets.
In order to improve the diagnosis accuracy of wireless sensor, a novel fault diagnosis for wireless sensor technology by twin support vector machine (TSVM) is proposed in the paper.
Twin SVM is a binary classifier that performs classification by using two nonparallel hyperplanes instead of the single hyperplane used in the classical SVM.
However, the parameter setting in the TSVM training procedure significantly influences the classification accuracy.
Thus, this study introduces PSO as an optimization technique to simultaneously optimize the TSVM training parameter.
The experimental results indicate that the diagnosis results for wireless sensor of twin support vector machine are better than those of SVM, ANN.
American Psychological Association (APA)
Ding, Mingli& Yang, Dongmei& Li, Xiaobing. 2013. Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1010490
Modern Language Association (MLA)
Ding, Mingli…[et al.]. Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine. Mathematical Problems in Engineering No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-1010490
American Medical Association (AMA)
Ding, Mingli& Yang, Dongmei& Li, Xiaobing. Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1010490
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010490