几种基于神经网络的GPS高程拟合方法比较OACSCD
Comparative Research on GPS Height Fitting Methods Based on Neural Network
为提高GPS大地高向正常高转换的精度，本文对目前研究较广泛的 BP神经网络方法、遗传神经网络方法和退火神经网络方法用于 GPS高程拟合的特点和拟合精度进行比较分析，为使用这些方法进行GPS高程拟合提供了参考。
Characteristics and precision of BP neural network,genetic neural network and annealing neural network applied in GPS height fitting were hereby compared and ana-lyzed to improve the precision of transforming GPS geodetic height into normal height,and improvement approaches were proposed with respect to all problems in GPS height fitting method.
牛志宏
长江工程职业技术学院，湖北 武汉 430212
天文与地球科学
GPS高程拟合BP神经网络遗传神经网络退火神经网络
GPS height fittingBP neural networkgenetic neural networkannealing neural network
《全球定位系统》 2014 (2)
64-67,4
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