A Modeling Method Based on Wavelet Support Vector Machine

被引：1
|
作者：
Wang, Shuzhou [1 ]
Meng, Bo [1 ]
Tian, Huixin [1 ]
机构：
[1] Tianjin Polytech Univ, Sch Elect Engn & Automat, Tianjin 300160, Peoples R China
来源：
2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5 | 2010年
关键词：
Support Vector Machine; Wavelet Kernel; Helicopter; Simulation Model;
D O I：
10.1109/CCDC.2010.5498645
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：3113 / 3116
页数：4
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