| 基于自适应Kalman滤波的BP神经网络及其在高程拟合中的应用 |
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| 引用本文： | 聂建亮 冯来平. 基于自适应Kalman滤波的BP神经网络及其在高程拟合中的应用[J]. 测绘科学与工程, 2007, 27(3): 27-30 |
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| 作者姓名： | 聂建亮 冯来平 |
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| 作者单位： | [1]长安大学硕士研究生 [2]不详 |
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| 基金项目： | 交通部科技项目（200531881203）和武汉大学地球空间环境与大地测量教育部重点实验室测绘基础研究基金（1469990324233-04-02）. |
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| 摘 要： | 针对传统BP神经网络容易发散、泛化能力差等问题，采用自适应Kalman滤波方法训练神经网络的连接权。与Kalman滤波训练连接权和传统的BP算法相比，该方法提高了BP神经网络计算精度，增强了泛化能力。实测数据的计算结果证明了该方法的可行性与有效性。
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| 关 键 词： | BP神经网络 自适应Kalman滤波 泛化能力 自适应因子 |
Network Based on Adaptive Kalman Application in Height Fitting |
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| Nie Jianliang, Feng Laiping. Network Based on Adaptive Kalman Application in Height Fitting[J]. Geomatic Science and Engineering, 2007, 27(3): 27-30 |
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| Authors: | Nie Jianliang Feng Laiping |
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| Abstract: | In this paper, adaptive Kalman filtering is proposed to train the weight of BP neural network for solving the problems of divergence and the low generalization ability. By comparisons, this method can improve the computing accuracy of BP newral network and generalization ability. It has been shown that BP based on adaptive Kalman filtering is feasible and efficient. |
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| Keywords: | BP neural network adaptive Kalman filtering generalization ability adaptive factors |
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