小波神经网络在遥感测温数据拟合中的应用研究
Application of Wavelet Analysis Based Neural Networks in the Data Fitting of Remote Sensing Temperature Measurement

作者: 伊晓东 , 孙鹏 :大连理工大学建设工程学部,辽宁 大连;

关键词: 小波神经网络BP神经网络遥感测温数据拟合Wavelet Neural Network BP Neural Network Remote Sensing Temperature Measurement Data Fitting

摘要: 将小波母函数嵌入人工神经网络的神经元形成紧致型小波神经网络,将此种网络用于遥感测温的数据拟合中,提升了纯粹的BP神经网络的拟合精度。结合红沿河核电站无人机红外测温试验,对其采集的一组温度数据采用小波神经网络进行拟合。对实验数据进行了统计分析,结果表明,小波神经网络能保证拟合误差在很小的范围之内,并且优于BP神经网络。本文中对于遥感测温数据的拟合误差控制在了0.4℃以内,可以满足测量要求。

Abstract: The wavelet mother function is embedded in the neurons of artificial neural network to form the compact wavelet neural network. This kind of network is applied to the data fitting of remote sensing temperature measurement, which could improve the fitting accuracy of the pure BP neu- ral network. Based on the infrared temperature measurement experiment at Hongyanhe nuclear plant using unmanned aerial vehicle, the data fitting is conducted for a group of obtained tempera- ture data. The statistical analysis is performed for the experimental data, and the results show that wavelet neural network could ensure the fitting errors in a small range, which is better than the BP neural network. In this paper, the fitting error of remote sensing temperature measurement is controlled at 0.4˚C which can meet the measurement requirements.

 

文章引用: 伊晓东 , 孙鹏 (2017) 小波神经网络在遥感测温数据拟合中的应用研究。 测绘科学技术, 5, 57-66. doi: 10.12677/GST.2017.52008

参考文献

[1] 贺佳惠, 梁春利, 李名松. 核电站近岸温度场航空热红外遥感测量数据处理研究[J]. 国土资源遥感, 2010(3): 51- 53.

[2] 王洛飞. 无人机低空摄影测量在城市测绘保障中的应用前景[J]. 测绘与空间地理信息, 2014(2): 217-219, 222.

[3] 金伟, 葛宏立, 杜华强, 等. 无人机遥感发展与应用概况[J]. 遥感信息, 2009(1): 88-92.

[4] 曹先革. 基于人工神经网络的GPS高程异常拟合方法研究[D]: [硕士学位论文]. 武汉: 中国地质大学(武汉), 2008.

[5] 付建东, 吴良才. 小波神经网络的改进及在GPS高程拟合中的应用研究[J]. 工程勘察, 2015, 43(2): 90-93.

[6] 伊廷华, 李宏男, 伊晓东, 等. 基于小波与神经网络的GPS周跳探测与修复[J]. 传感技术学报, 2007, 20(4): 897- 902.

[7] 王江荣. 基于小波分析的神经网络在混凝土测强曲线拟合中的应用[J]. 工程质量, 2011, 29(12): 63-65.

分享
Top