| 基于RBF神经网络的GPS高程拟合方法的研究 |
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| 引用本文： | 张红华.基于RBF神经网络的GPS高程拟合方法的研究[J].北京测绘,2014(4):5-8. |
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| 作者姓名： | 张红华 |
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| 作者单位： | 黑龙江科技大学矿业工程学院,黑龙江哈尔滨,150022 |
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| 摘 要： | GPS高程拟合一直是工程应用中的一个研究热点,其中神经网络拟合方法得到了广泛的应用。本文利用RBF神经网络模型进行GPS高程拟合实验,主要针对模型中隐含节点数和最佳SPREAD值的确定进行实验研究,并利用MATLAB神经网络工具箱实现了GPS高程拟合。同时,将RBF神经网络拟合结果与BP网络拟合结果进行对比分析,结果表明,RBF网络拟合效果要优于BP网络,得到的拟合精度要高。
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| 关 键 词： | 神经网络 RBF BP GPS高程拟合 拟合精度 |
Research on the Method of GPS Elevation Fitting Based on RBF Neural Network |
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| ZHANG Hong-hua.Research on the Method of GPS Elevation Fitting Based on RBF Neural Network[J].Beijing Surveying and Mapping,2014(4):5-8. |
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| Authors: | ZHANG Hong-hua |
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| Institution: | ZHANG Hong-hua (College of Mining Engineering, Heilongjiang University of Science and Technology, Harbin, Heilongjiang 150027, China) |
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| Abstract: | GPS elevation fitting is always a hotspot in engineering application. Neural network fitting methods have been used widely. In this paper, it uses the RBF neural network model for GPS elevation fitting test. The test is studied in order to determine the number of hidden nodes and the optimal value of SPREAD. Using MATLAB neural network toolbox, it realizes the GPS elevation fitting. By using RBF neural network fitting results compared with the BP network fitting results, BF network fitting is better than the BP network, the fitting precision is to be higher. |
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| Keywords: | neural network RBF BP GPS elevation fitting fitting accuracy |
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