Panaitescu A, Moraru A. Research on the instabilities in the aluminum electrolysis cell[C] Light Metals. San Diego, 2003: 359-366. [2] Urata N. Magnetics and metal pad instability[C] Light Metals. New York, 1985: 581-589. [3] Kurenkov A, Thess A, Zikanov O. Stability of aluminum reduction cell with mean flow [J]. Magneto hydro dynamics, 2004, 40(2):3-13. [4] LI He-song, MEI Chi, ZHOU Nai-jun. Diagnosis of working conditions of an aluminum reduction cell based on wavelet packets and fuzzy neural network [J]. Chemical Engineering and Processing, 2006, 45(12):1074-1080. [5] 刘庆华, 张为公, 龚宗洋. 广义回归神经网络在汽车换档机械手运动轨迹测量中的应用 [J]. 仪器仪表学报, 2008, 29(2): 361-364. [5] LIU Q H, ZHANG W G, GONG Z Y. Application of general regression neural network (GRNN) in motion track measurement of auto mobile gear shifting manipulator [J]. Chinese Journal of Scientific Instrument, 2008, 29 (2): 361-364. [6] VAPNIK V N. An overview of statistical learning theory [J].IEEE Trans Neural Networks, 1999, 10(5): 988-999. [7] SUYKENS J A K, VANDEW ALLE J. Least squares support vector machine classifiers [J]. Neural Processing Letters, 1999, 9(3): 293-300. [8] J A. K. Suykens, De. Brabanter J, Least squares support vector machines, Singapore: World Scientific Publishing Co Pte Lte, 2002. [9] Stasiak, Magdalena, Sikora, Jan, "Principal component analysis and artificial neural network approach to electrical impedance tomography problems approximated by multi-region boundary element method," Engineering Analysis with Boundary Elements, 2007. 31 (8):713-720. [10] 刘毅, 王海清, 李平. 用于发酵过程存线建模的自适应局部最小二乘支持向量机回归方法[J].化工学报, 2008, 59(8): 2052-2057. [10] LIU Yi,WANG H Q,LI P. Adaptive local learning based least squares support vector regression with application to online modeling [J]. Journal of Chemical Industry and Engineering, 2008, 59(8): 2052-2057.