A Modeling Method Based on Wavelet Support Vector Machine

摘要：

Neural networks with good nonlinear mapping abilities can be applied to build simulation model of helicopter. But they have some difficulties such as hardness of selecting network structure, slow convergence speed, local minimum, and over-fitting. To avoid above problems, a modeling method based on Wavelet Support Vector Machine (WSVM) is proposed. Marr wavelet is used to construct wavelet kernel. And the rationality of the multidimensional wavelet kernel is proved. Based on pretreatment of practical flight data, rotational speed model for landing process of helicopter with rotor self-rotating is built with WSVM. Compared with neural network model, WSVM model possess some advantages such as simple structure, fast convergence speed and high generalization ability.

关键词： Support Vector Machine Wavelet Kernel Helicopter Simulation Model

作者: Shuzhou Wang Bo Meng Huixin Tian

作者单位: School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300160, China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 3113-3116

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）