摘要
为提高形变预测的精度,提出将主成分分析与改进的BP神经网络相结合用于形变监测数据处理。通过编程实现该算法,并用实测数据进行验证,结果表明:与其他方法相比,基于主成分分析的改进BP神经网络能取得更好的预测效果。
In order to improve deformation forecasting precision, application of principal component analysis and improved BP neural network in deformation monitoring is proposed. For the verification if the new method can enhance the precision and reliability of forecasted data, the proposed algorithm is programmed and verified by use of measured data. The results show that compared with other methods, the improved BP neural network based on principal component analysis can achieve better foresting results.
出处
《大地测量与地球动力学》
CSCD
北大核心
2008年第3期72-76,共5页
Journal of Geodesy and Geodynamics
关键词
形变
主成分分析
神经网络
预测
形变监测
deformation
principal component analysis
neural network
forecasting
deformation monitoring
