Referenced Items are not available for this document.
With rough set theory for knowledge reduction capability and C4.5 decision tree algorithm for fast classification of strengths, an improved rough set-decision tree model for fault diagnosis of wind generation system is built. The results show that the proposed method can not only decreases the workload of feature datum extraction, but also identifies the fault patterns rapidly and accurately, and it exhibits better engineering practicality comparing with the C4.5-based method.
Published in:
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Date of Conference: 8-10 Aug. 2011
- Page(s):
- 3630 - 3633
- Print ISBN:
- 978-1-4577-0535-9
- INSPEC Accession Number:
- 12259674
- Conference Location :
- Deng Leng
- Digital Object Identifier :
- 10.1109/AIMSEC.2011.6010152
- Product Type:
- Conference Publications
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