大地测量与地球动力学2012，Vol.32Issue(6)：103-105,110,4.
基于二次曲面和BP神经网络组合模型的GPS高程异常拟合
COMBINED MODEL IN HEIGHT ANOMALY FITTING
摘要
Abstract
The combined model based on the quadratic surface model and BP neural network model is applied to the GPS height anomaly fitting, while the combination is determined from the variance reciprocal method and general regression neural network (GRNN). The GPS elevation data in a certain area is used, the results show that both the accuracy and reliability with the combined model are more superior to the single models, and the fitting accuracy with the combined model based on general regression neural network ( GRNN) is better than that with the combined model based on the variance reciprocal method.关键词
二次曲面模型/BP神经网络模型/高程异常/广义回归神经网络/方差倒数法Key words
quadratic surface model/ BP neutral network model/ height anomaly/ general regression neural network/ variance reciprocal method分类
天文与地球科学引用本文复制引用
王小辉,王琪洁,丁元兰,刘建..基于二次曲面和BP神经网络组合模型的GPS高程异常拟合[J].大地测量与地球动力学,2012,32(6):103-105,110,4.基金项目
国家自然科学基金(U1231105,10878026) （U1231105,10878026）
