提出一种综合的多面函数参数自适应选取方法。该方法利用核函数阶数和平滑因子存在最优值以及核函数结点分布应符合高程异常变化趋势的特点,综合利用正交化算法选取核函数结点以及二维粒子群算法确定最佳阶数和平滑因子,实现多面函数参数的完全自适应选取。将该方法应用于地形起伏差异不同的2个测区,结果表明,相比传统经验性方法和部分参数自适应方法,该方法用于GPS高程拟合的精度和可靠性更高。"/> We propose an integrated self-adaptive parameter selection scheme. Our method takes advantage of the fact that the kernel function order and the smoothing factor are in an optimal range, and the distribution of kernel function nodes should be in accordance with terrain characteristics. By combining the orthogonalization algorithm to select the nodes and the two-dimensional particle swarm algorithm to determine the optimal order and smoothing factor, we realize the fully self-adaptive selection of multiquadric function parameters. Two areas with different topographic relief are selected for GPS elevation fitting; the results show that accuracy and reliability of our method are both better than the traditional empirical parameter selection and partially self-adaptive parameter selection method."/> Application of Self-Adaptive Parameter Selection for Multiquadric Function in GPS Elevation Fitting
大地测量与地球动力学
 
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Application of Self-Adaptive Parameter Selection for Multiquadric Function in GPS Elevation Fitting
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