prediction of satellite clock bias based on wavelet transform andleast squares support vector machines
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摘要: 提出了一种基于小波变换和最小二乘支持向量机的卫星钟差预报方法 首先通过小波变换把钟差时间序列分解成具有不同频率特征的分量然后根据各分量的特点构建不同的最小二乘支持向量机模型进行预报最后将各分量的预报结果进行叠加得到最终的钟差预报值 实验结果表明该方法的预报效果优于单一的最小二乘支持向量机模型以及常规的二次多项式模型和灰色系统模型Abstract: this paper proposes a novel method for prediction of satellite clock bias scb based onwavelet transform and least squares support vector machineslssvm．the method first decomposesscb time series into different fre quency components through the wavelet transform al gorithm．thenaccording to the different characteristics of the decomposed componentsthe proper lssvm are constructed to predict the components．finall ythe final prediction value of scb is yielded by the lineari ty super position for the res pective predicted result．the experiment shows that the proposed method can improve the prediction accurac y of scb when the quadratic pol ynomial qp modelgm11model and lssvm model
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