基于误差同步预测的SVM金融时间序列预测方法

[1] 基于SVM的多变量股市时间序列预测研究 [J]. 计算机应用与软件, 2010, 27 (06) : 191 - 194+209

[2] 基于支持向量回归神经网络的时间序列预测 [J]. 系统仿真学报, 2008, (15) : 4025 - 4030

[3] 基于小波变换域的SVM股市时间序列预测算法 [J]. 科学技术与工程, 2008, (12) : 3171 - 3174

[4] 经验模态分解方法及其实现 [J]. 计算机工程与应用, 2006, (32) : 44 - 47

[5] A novel algorithm of artificial immune system for high-dimensional function numerical optimization[J]. DU Haifeng 1,2*, GONG Maoguo1, JIAO Licheng1 and LIU Ruochen1(1. Institute of Intelligent Information Processing and Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China;2. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China).Progress in Natural Science. 2005(05)

[6] Using support vector machines for time series prediction[J] . U Thissen,R van Brakel,A.P de Weijer,W.J Melssen,L.M.C Buydens.Chemometrics and Intelligent Laboratory Systems . 2003 (1)

[7] Modified support vector machines in financial time series forecasting[J] . Francis E.H. Tay,L.J. Cao.Neurocomputing . 2002 (1)

[8] A NEW VIEW OF NONLINEAR WATER WAVES: The Hilbert Spectrum1[J] . Norden E. Huang,Zheng Shen,Steven R. Long.Annual Review of Fluid Mechanics . 1999 (1)

[9] The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971): : 903 - 995

[10] SUPPORT-VECTOR NETWORKS [J]. MACHINE LEARNING, 1995, 20 (03) : 273 - 297

[1] 基于SVM的多变量股市时间序列预测研究 [J]. 计算机应用与软件, 2010, 27 (06) : 191 - 194+209

[2] 基于支持向量回归神经网络的时间序列预测 [J]. 系统仿真学报, 2008, (15) : 4025 - 4030

[3] 基于小波变换域的SVM股市时间序列预测算法 [J]. 科学技术与工程, 2008, (12) : 3171 - 3174

[4] 经验模态分解方法及其实现 [J]. 计算机工程与应用, 2006, (32) : 44 - 47

[5] A novel algorithm of artificial immune system for high-dimensional function numerical optimization[J]. DU Haifeng 1,2*, GONG Maoguo1, JIAO Licheng1 and LIU Ruochen1(1. Institute of Intelligent Information Processing and Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China;2. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China).Progress in Natural Science. 2005(05)

[6] Using support vector machines for time series prediction[J] . U Thissen,R van Brakel,A.P de Weijer,W.J Melssen,L.M.C Buydens.Chemometrics and Intelligent Laboratory Systems . 2003 (1)

[7] Modified support vector machines in financial time series forecasting[J] . Francis E.H. Tay,L.J. Cao.Neurocomputing . 2002 (1)

[8] A NEW VIEW OF NONLINEAR WATER WAVES: The Hilbert Spectrum1[J] . Norden E. Huang,Zheng Shen,Steven R. Long.Annual Review of Fluid Mechanics . 1999 (1)

[9] The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J]. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971): : 903 - 995

[10] SUPPORT-VECTOR NETWORKS [J]. MACHINE LEARNING, 1995, 20 (03) : 273 - 297