Satellite fault diagnosis using support vector machines based on a hybrid voting mechanism.
The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassific...
| Publicado en: | Scientific World Journal pp. 582042 - 582043 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103845736&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103845736 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103845736 NLM25215324 2012727980 10.1155/2014/582042 NLM25215324 PMC4146359 103845736 ppf: 582042 ppct: 1 formats: tig: atl: Satellite fault diagnosis using support vector machines based on a hybrid voting mechanism. aug: au: Yin, Hong Yang, Shuqiang Zhu, Xiaoqian Jin, Songchang Wang, Xiang affil: College of Computer, National University of Defense Technology, Changsha 410073, China ; Xiangyang School for NCOs, Xiangyang 441118, China. sug: subj: Algorithms Models, Theoretical Telecommunications Equipment and Supplies ab: The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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