基于LS-SVM的GPS高程转换及其抗差性研究

GPS Height Conversion Based on LS-SVM and Its Robustness

论述LS-SVM的原理及算法,并结合GPS高程拟合问题,建立了相应的GPS高程拟合模型。利用实例数据,从模型精度角度与多项式拟合、BP神经网络拟合的结果进行对比分析,并选取LS-SVM和BP神经网络进行了模型抗差性分析。结果表明,LS-SVM拟合具有较高的拟合精度和较好的抗差性。

This paper discussed the algorithm of LS-SVM,and established the GPS elevation iing model through combine with the problem of GPS elevation fifing.Through a set of experiment data,it compared and analyzed the result of polynomial fitting,BP neural network itting from the aspect of accuracy,also chose LS-SVM and BP neural network to analysis the robustness.The result shows that the LS-SVM is more promising and with good robust.