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Fitting the GPS/leveling Quasi-geoid Using Bayesian-regulation BP Neural Network

机译:使用贝叶斯调节BP神经网络拟合GPS /水平准大地区

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The 2.5'×2.5'resolution local quasi-geoid is calculated using the global gravity field model and GPS/leveling data of region which points spacing is about 10km with the Bayesian- regulation BP neural network in this paper. The inner and outer precision of quasi-geoid are both superior 0.05m. The result indicat that the Bayesian regulation BP neural network could improve the precision of fitting and restrain the over-fitting in fitting. The region quasi-geoid excelled than 0.05m can be computed using the global gravity field model and about 10km baseline GPS/leveling data in smoothness region.
机译:2.5'×2.5'Resolution局部准大地区使用全球重力场模型和GPS /调平数据,其中间距与贝叶斯 - 调节的BP神经网络在本文中大约10km。拟麻醉剂的内部和外部精度均优越0.05米。结果表明,贝叶斯调节BP神经网络可以提高配件的精度,并限制配件过度装配。可以使用全局重力场模型和平滑区域中大约10km基线GPS /调平数据来计算Quasi-Geoid优先于0.05米。

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