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	Fault diagnosis of transformer based on random forest
	Chen, Xi ; Cui, Hongmei ; Luo, Linkai ; Luo LK(罗林开)
	2011
关键词	Decision trees Neural networks Pattern recognition
英文摘要	Conference Name:2011 4th International Conference on Intelligent Computation Technology and Automation, ICICTA 2011. Conference Address: Shenzhen, Guangdong, China. Time:March 28, 2011 - March 29, 2011.; Hunan University; Changsha University of Science and Technology; Hunan University of Science and Technology; Intelligence Computation Technology and Automation Society; Fault diagnosis of transformer in power system is studied in this paper. Considering the excellent performances of Random Forest (RF) in pattern recognition, we apply RF to construct a diagnosis model to predict the situation of transformer. The experiments of fault diagnosis for some real transformers show that RF obtains a better result in prediction accuracy and stability than traditional Back Propagation neural network does. In addition, the order of influence factors given by RF is helpful in fault diagnosis. ? 2011 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/ICICTA.2011.40
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/87031]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Chen, Xi,Cui, Hongmei,Luo, Linkai,et al. Fault diagnosis of transformer based on random forest. 2011-01-01.

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