Application of knowledge roughness-based multivariate decision tree in transformer fault diagnosis system

Dianli Zidonghua Shebei / Electric Power Automation Equipment

Volumn 25, Issue 10, 2005, Pages 43-

  Li, Jing Hua ^a   Li, Ran ^a  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

Author keywords

Fault diagnosis; Knowledge roughness; Multivariate tree; Rough set theory; Transformer

Indexed keywords

DATA STRUCTURES; FAULT TOLERANT COMPUTER SYSTEMS; KNOWLEDGE BASED SYSTEMS; OPTIMIZATION; ROUGH SET THEORY; SELF ORGANIZING MAPS;

DECISION TREE; FAULT DIAGNOSIS; FAULT DIAGNOSIS SYSTEM; KNOWLEDGE ROUGHNESS; MULTIVARIATE TREE;

DECISION THEORY;

EID: 33749463482     PISSN: 10066047     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (6)

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2. WANG Nan, LÜ Fang-cheng, LI He-ming. Application of rough set to build transformer fault diagnosis model based on multivariate decision tree [J]. Advanced Technology of Electrical Engineering and Energy, 2004, 23 (1): 21-24, 33.
3. BUNTINE W, NIBLETT T. A further comparison of splitting rules for decision-tree induction [J]. Machine Learning, 1992, (8): 75-85.
4. WANG Jian-yuan, JI Yan-chao. Application of fuzzy Petri nets knowledge representation in electric power transformer fault diagnosis [J]. Proceedings of the CSEE, 2003, 23 (1): 121-125.