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Modelling of chaotic systems based on modified weighted recurrent least squares support vector machines 被引量:3

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出处 《Chinese Physics B》 SCIE EI CAS CSCD 2004年第12期2045-2052,共8页 中国物理B(英文版)
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参考文献17

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同被引文献13

  • 1阎威武,常俊林,邵惠鹤.一种贝叶斯证据框架下支持向量机建模方法的研究[J].控制与决策,2004,19(5):525-528. 被引量:21
  • 2姜云春,邱静,刘冠军.基于LS-SVM建模与预测的液压伺服系统故障诊断[J].液压与气动,2006,30(6):44-47. 被引量:2
  • 3DONG Min LIU Cai.Design of Fault Diagnosis Observer for HAGC System on Strip Rolling Mill[J].Journal of Iron and Steel Research(International),2006,13(4):27-31. 被引量:7
  • 4Suykens J A K, Van Gestel T. De Brabanter J, et al. Least squares support vector machines[M]. Singapore:World Scientific Publishing Co Pte, 2002.
  • 5Suykens J A K, Branbamer J K, Lukas L, et al, Weighted least squares support vector machine: Robustness and sparse approximation[ J ]. Neuro Computing, 2002, 48(1): 85-105.
  • 6Chen A J, Song Z H, Li P. Soft sensor modeling base on DICA-SVR[C]. Advances in Intelligent Computing, PT 1. Hefei, 2005, 3644: 868-877.
  • 7王连详,方德植,张鸣镛,等.数学手册[M].北京:高等教育出版社,2004:798-801.
  • 8VapnikVN.统计学习理论的本质[M].北京:清华大学出版社,2000..
  • 9唐照千 黄文虎.振动与冲击手册[M].北京:国防工业出版社,1990..
  • 10Suykens J A K.Nonlinear modeling and support vector machine[C] // Proc of the 18th IEEE Conf on Instrumentation and Measurement Technology.Piscataway,USA:IEEE,2001:287-294.

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