| 最小二乘支持向量机在GPS高程拟合中的应用 |
| |
| 引用本文： | 任超,李和旺. 最小二乘支持向量机在GPS高程拟合中的应用[J]. 工程勘察, 2012, 0(7): 55-57 |
| |
| 作者姓名： | 任超 李和旺 |
| |
| 作者单位： | 桂林理工大学测绘地理信息学院;广西空间信息与测绘重点实验室 |
| |
| 基金项目： | 国家自然科学基金项目(41071294);广西自然科学基金资助项目(编号:桂科自0640178);广西科学基金资助项目(编号:桂科基0991023) |
| |
| 摘 要： | 本文论述了最小二乘支持向量机(LS-SVM)的算法,提出了基于最小二乘支持向量机进行GPS高程拟合的方法,并在MATLAB中编制了相应的LS-SVM程序,建立了相应的GPS高程拟合模型。以实例数据讨论了LS-SVM的GPS高程拟合的分析方法,通过与多项式拟合、BP神经网络拟合、GA-BP神经网络拟合的结果比较,可知LS-SVM的拟合精度较高。
|
| 关 键 词： | GPS LS-SVM 神经网络 高程拟合 |
Application of least squares support vector machine in GPS leveling |
| |
| Ren Chao,Li Hewang. Application of least squares support vector machine in GPS leveling[J]. Geotechnical Investigation & Surveying, 2012, 0(7): 55-57 |
| |
| Authors: | Ren Chao Li Hewang |
| |
| Affiliation: | 1,2(1.College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541004,China; 2.Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541004,China) |
| |
| Abstract: | This paper discussed the algorithm of support vector regression,proposed the method of GPS leveling based on the least squares support vector machine,and compiled programs for GPS leveling by using the MATLAB toolbox.Through a set of experimental data,the effectiveness of our method was discussed.Compared with results of polynomial fitting,BP neural network fitting and GA-BP neural network fitting,the result of LS-SVM is more promising. |
| |
| Keywords: | GPS LS-SVM neural network GPS leveling |
| 本文献已被 CNKI 等数据库收录！ |
|
