Tunnel Surrounding Rock Displacement Prediction Using Support Vector Machine
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Jian Sun | Jin-Bao Yao | Bao-Zhen Yao | Cheng-Yong Yang | Jian Sun | Jinbao Yao | B. Yao | C. Yang
[1] Xin Xu,et al. Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis , 2009, Int. J. Comput. Intell. Syst..
[2] David F. Hendry,et al. Non-Parametric Direct Multi-Step Estimation for Forecasting Economic Processes , 2004 .
[3] S. Sorooshian,et al. Shuffled complex evolution approach for effective and efficient global minimization , 1993 .
[4] Vladimir Vapnik,et al. An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.
[5] Yourong Li,et al. Short-term fault prediction based on support vector machines with parameter optimization by evolution strategy , 2009, Expert Syst. Appl..
[6] Martin Fodslette Møller,et al. A scaled conjugate gradient algorithm for fast supervised learning , 1993, Neural Networks.
[7] Baozhen Yao,et al. Bus Arrival Time Prediction Using Support Vector Machines , 2006, J. Intell. Transp. Syst..
[8] Sung-Do Chi,et al. Evolutionary Parameter Estimation Algorithm for Combined Kernel Function in Support Vector Machine , 2004, AWCC.
[9] Bo Yu,et al. Hybrid Model for Prediction of Bus Arrival Times at Next Station , 2010 .
[10] S. Sorooshian,et al. Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .
[11] John A. Nelder,et al. A Simplex Method for Function Minimization , 1965, Comput. J..
[12] Jie Liu,et al. A multi-step predictor with a variable input pattern for system state forecasting , 2009 .
[13] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[14] S. A. Billings,et al. A new direct approach of computing multi-step ahead predictions for non-linear models , 2003 .
[15] Amir F. Atiya,et al. Multi-step-ahead prediction using dynamic recurrent neural networks , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[16] Yu Zhao,et al. Application of Grey Majorized Model in Tunnel Surrounding Rock Displacement Forecasting , 2005, ICNC.
[17] Kwok-wing Chau,et al. A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity , 2006 .
[18] Yu Bin,et al. Bus Arrival Time Prediction Using Support Vector Machines , 2006 .
[19] W. Schubert,et al. Displacement Monitoring in Tunnels - an Overview , 2002 .
[20] Robert W. Harrison,et al. Granular Decision Tree and Evolutionary Neural SVM for Protein Secondary Structure Prediction , 2009, Int. J. Comput. Intell. Syst..
[21] André Carlos Ponce de Leon Ferreira de Carvalho,et al. Evolutionary tuning of SVM parameter values in multiclass problems , 2008, Neurocomputing.
[22] Donath Mrawira,et al. Shuffled complex evolution algorithms in infrastructure works programming , 2004 .
[23] Wulf Schubert,et al. Prediction Of Displacements In Tunnelling , 2000 .
[24] W. Price. Global optimization algorithms for a CAD workstation , 1987 .
[25] Chuntian Cheng,et al. Using support vector machines for long-term discharge prediction , 2006 .
[26] Francis Eng Hock Tay,et al. Support vector machine with adaptive parameters in financial time series forecasting , 2003, IEEE Trans. Neural Networks.
[27] Soroosh Sorooshian,et al. Optimal use of the SCE-UA global optimization method for calibrating watershed models , 1994 .
[28] Chuntian Cheng,et al. A new indirect multi-step-ahead prediction model for a long-term hydrologic prediction , 2008 .
[29] Chih-Jen Lin,et al. A Practical Guide to Support Vector Classication , 2008 .
[30] Cheng-Lung Huang,et al. A GA-based feature selection and parameters optimizationfor support vector machines , 2006, Expert Syst. Appl..
[31] Huicheng Zhou,et al. Ice breakup forecast in the reach of the Yellow River: the support vector machines approach , 2009 .