摘要
通过向20°/20°Z形试验仿真数据中添加随机噪声,得到含噪声的试验数据;随后,应用最小二乘支持向量回归机(Least Square-Support Vector Regression,LS-SVR)对经过小波去噪的试验数据和含噪声的试验数据进行分析,辨识了船舶操纵运动二阶线性响应模型中的操纵性指数。将由去噪试验数据和含噪试验数据得到的20°/20°Z形试验预报结果同20°/20°Z形试验仿真数据进行对比,验证了小波去噪在对含噪声的Z形试验数据进行去噪处理的有效性。
By adding some random noise into the simulated 20°/20° zigzag test data,the polluted test data are obtained.Wavelet denoising is then applied to denoise the polluted data.By analyzing the denoised data and the polluted data,Least Square-Support Vector Regression（LS-SVR） is applied to identify the manoeuvring indices of the second-order linear response model.The prediction results of 20°/20° zigzag test by using the denoised test data and the polluted test data are compared with the simulated test data to demonstrate the validity of wavelet denoising in the denoising of the polluted test data.
出处
《船舶力学》
EI
北大核心
2011年第6期616-622,共7页
Journal of Ship Mechanics
基金
Supported by the National Natural Science Foundation of China(Grant Nos.50979060,51079031)
the Foundation of National Science and Technology Key Laboratory of Hydrodynamics(GrantNo.9140C2201091001)
关键词
船舶操纵
参数辨识
小波去噪
最小二乘支持向量回归机
ship manoeuvring
parameter identification
wavelet denoising
LS-Support Vector Regression（LS-SVR）
