Ma Junshui, Perkins S. Online novelty detection on temporal sequences[C]. Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington D C,OSA,August, 24-27,2003.
[4]
Bishop C M. Pattern recognition and machine learning[M]. New York:Springer, 2006.
[5]
Smola A J, Scholkopf B. A tutorial on support vector regression[J]. Statistics and Computing, 2004,14(3):199-222.
[6]
Wand M P,Jones M C. Kernel smoothing[M]. London: Chapman and Hall, 1995.
[7]
孟庆芳.非线性动力系统时间序列分析方法及其应用研究[D].济南:山东大学,2008.
[8]
Stone R, Taylor M. Time series models in statistical process control:Considerations of applicability[J]. The Statistician, 1995, 44(2): 227-234.
[9]
Ma Junshui, Perkins S. Time-series novelty detection using one-class support vector machines[C]. Proceedings of the International Joint Conference on Neural Networks, IEEE, Portland,Oregon,USA,July 20-24,2003.
[10]
Liu Xuan, Zhang Pengzhu, Zeng Dajun. Sequence matching for suspicious activity detection in anti-money laundering[M]//Mehrotras,zeng DD,chen H C.Intelligence and Security Informatics. Berlin: Springer Verlag, 2008: 50-61.
Alwan L C, Roberts H V. Time-series modeling for statistical process control[J]. Journal of Business and Economic Statistics, 1988, 6(1): 87-95.
[15]
Tay F E, Cao L. Application of support vector machines in financial time series forecasting[J]. International Journal of Management Science, 2001, 29(4):309-317.
[16]
Krollner B, Vanstone B, Finnie G. Financial time series forecasting with machine learning techniques: A survey[C].Proceedings of 18th European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning, Bruges(Belgium), April 28-30,2010.
[17]
Packard N H, Crutchfield J P,Farmers J D, et al. Geometry from a time series[J]. Physical review letters, 1980, 45(9):712-716.
[18]
Small M. Applied nonlinear time series analysis[M]. Singapore: World Scientific, 2005.