| 似大地水准面的支持向量机模型研究 |
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| 引用本文： | 郝伟涛,郭向前,米川.似大地水准面的支持向量机模型研究[J].测绘科学,2012(4):22-23,63. |
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| 作者姓名： | 郝伟涛 郭向前 米川 |
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| 作者单位： | 河南省地质测绘总院 |
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| 摘 要： | 支持向量机(SVM)是一种基于结构风险最小化原理的学习技术,也是一种新的具有较好泛化性能的回归方法。本文简要介绍了SVM原理,针对大面积复杂似大地水准面的确定问题,仅依据测区的GPS水准实测数据,利用SVM方法整体建模。通过工程实例并与神经网络模型进行对比,证实了SVM似大地水准面模型的可靠性。
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| 关 键 词： | GPS水准 似大地水准面 支持向量机模型 |
Study on Support Vector Machine model for determination of quasi-geoid |
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| HA Wei-tao,GUO Xiang-qian,MI Chuan.Study on Support Vector Machine model for determination of quasi-geoid[J].Science of Surveying and Mapping,2012(4):22-23,63. |
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| Authors: | HA Wei-tao GUO Xiang-qian MI Chuan |
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| Institution: | g(Henan Geological Surveying and Mapping,Zhengzhou 450006,China) |
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| Abstract: | ion: Support Vector Machine(SVM) is a learning technique based on the structural risk minimization principle,and it is also a class of regression method with good generalization ability.Aiming at the determination of large area complex quasi-geoid,only depending on the GPS leveling data,this paper first introduced the principle of SVM briefly,then chose the parameters and built the quasi-geoid model.Through taking an example and comparing with the Neural Network model,the correctness and effectiveness of the SVM model were demonstrated finally. |
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| Keywords: | GPS leveling quasi-geoid Support Vector Machine model |
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