姚兆明.人工冻土温度场影响因素灵敏度分析.水文地质工程地质，2006,33(3):38-40.(Yao Zhaoming. The sensitivity analysis of factors affecting the temperature field development in artificial freezing soils. Hydrogeology & Engineering Geology,2006,33(3):38-40.(in Chinese))
[2]
Vapnik V N. Statistical Learning Theory[M]. New York: John and Wiley,1998.
[3]
汪仁和、徐士良．冻结壁温度场模型试验及其导热系数反分析[J]．安徽理工大学学报(自然科学版)2003,23(4): 18-22．(Wang Renhe,Xu Shiliang. Modeling test of temperature field of freezing wall and inverse heat conduction problem[J]. Journal of Anhui University of Science and Technology(Natural Science),2003，23(4):18-22. (in Chinese))
[4]
Platt J C. Sequential minimum optimization: A fast algorithm fortraining support machines[A]. In: Skolkpf B,Burges C J C,Smola AJ ed. Advanced in Kernel Methods-support Vector Learning[C]. Cambridge,MA: MIT Press,1998. 185-208.
[5]
张浩然 韩正之 李昌刚. 基于支持向量机的非线性系统辨识[J]. 系统仿真学报，2003,15(1): 119-121. (Zhang Haoran,Han Zhengzhi,Li Changgang. Support vector machine based nonlinear systems identification[J]. Journal of system simulation: 2003,15(1):119-121.(in Chinese))
[6]
赵洪波，冯夏庭. 非线性位移时间序列预测的进化-支持向量机方法及其应用[J]. 岩土工程学报,2003,22(10): 631-633.(Zhao Hongbo,Feng Xiating. Study and application of genetic-support vector machine for nonlinear displacement time series forecasting[J]. Chinese Journal of Geotechnical Engineering,2003,22(10):631-633. (in Chinese))
[7]
姚兆明，周启俊.人工冻土温度场的智能方法预测[J].安徽理工大学学报(自然科学版).2005,25(3):26-29.(YAO Zhaoming,ZHOU Qijun. The intelligent method forecasting artificial frozen temperature field. Journal of Anhui University of Science and Technology (Natural Science). 2005,25(3):26-29)
