Zhang Jianguang, Zhou Hao, Xiang Canfang. Application of super SAB ANN model for transformer fault diagnosis[J]. Transactions of China Electrotech- nical Society, 2004, 19(7): 49-52, 58.
[6]
Bishop C M. Pattern Recognition and Machine Learning[M]. Singapore: Springer, 2006.
[7]
Rasmussen C E, Williams C K I. Gaussian processes for machine learning[M]. Cambridge/London: The MIT Press, 2006.
[8]
Saitta L. Machine learning: a technological roadmap [R]. The Netherlands: Univ. of Amsterdam, 2000.
[9]
Ling C X, Sheng V S. A comparative study of cost-sensitive classifiers[J]. Chinese J of Computers, 2007, 30(8): 1023-1211.
[10]
Diamantini C, Potena D. Bayes vector quantizer for classimbalance problem[J]. IEEE Trans on Knowledge and Data Engineering, 2009, 21(5): 638-651.
[11]
Girolami M, Rogers S. Variational Bayesian multino- mial probit regression with Gaussian process priors[J]. Neural Computation, 2006, 18(8): 1790- 1817.
Zhao Wenqing, Zhu Yongli, Zhang Xiaoqi. Combina- tional forecast for transformer faults based on support vector machine[J]. Proceedings of the CSEE, 2008, 28(25): 14-19.
[14]
Tang W H, Wu Q H. Condition monitoring and assessment of power transformers using computational intelligence[M]. New York: Springer-Verlag Press, 2011, 95-104.
[15]
Sheng Weifei, Xiao Binzhang. Fault diagnosis of power transformer based on support vector machine with genetic algorithm[J]. Expert Systems with Applications, 2009, 36(8): 11352-11357.
Li Zhong, Yuan Jinsha, Zhang Liwei. Fault diagnosis for power transformer based on the self-organization antibody net[J]. Transactions of China Electrotechnical Society, 2010, 25(10): 200-206.
[18]
Seeger M. Gaussian processes for machine learning[J]. International Journal of Neural Systems, 2004, 14(2): 69-106.
[19]
Kuss M, Rasmussen C E. Assessing approximate inference for binary Gaussian process classification[J]. Journal of Machine Learning Research, 2005, 6: 1679-1704.
[20]
Nickisch H, Rasmussen C E. Approximations for binary Gaussian process classification[J]. Journal of Machine Learning Research, 2008, 9: 2035-2078.
[21]
Bermak A, Belhouari S B. Bayesian learning using gaussian process for gas identification[J]. IEEE Transactions on Instrumentation and Measurement, 2006, 55(3): 787-792.
Zheng Haiping, Sun Caixin, Li Jian, et al. A model and method of degree of grey incidence analysis on transformer fault diagnosis[J]. Proceedings of the CSEE, 2001, 21(10): 106-109.
