测绘通报 ›› 2019, Vol. 0 ›› Issue (1): 85-88.doi: 10.13474/j.cnki.11-2246.2019.0017

• 技术交流 • 上一篇    下一篇

量子粒子群BP神经网络在GNSS高程转换中的应用分析

韩红超   

  1. 宁波市测绘设计研究院, 浙江 宁波 315100
  • 收稿日期:2018-04-12 修回日期:2018-09-14 出版日期:2019-01-25 发布日期:2019-02-14
  • 作者简介:韩红超(1985-),男,硕士,高级工程师,国家注册测绘师,主要从事CORS推广服务、基础测绘应用研究、地面沉降监测及灾害防治等工作。E-mail:573568837@qq.com

The research and application of quantum particle swarm BP neural network in GNSS elevation transformation

HAN Hongchao   

  1. Mapping Design Academy of Ningbo, Ningbo 315100, China
  • Received:2018-04-12 Revised:2018-09-14 Online:2019-01-25 Published:2019-02-14

摘要: 提出了一种基于量子粒子群神经网络(QPSO-BP)模型的GNSS高程转换方法,通过建立GNSS点平面坐标与正常高之间的三层QPSO-BP数学模型而实现GNSS高程转换。试验分析结果表明,该方法全局迭代进化搜索能力高、稳健性强、拟合及预测精度高,在GNSS高程转换方面具有良好的有效性与先进性。

关键词: 量子粒子群, BP神经网络, GNSS高程转换

Abstract: In this paper, a GNSS elevation transformation method based on quantum particle swarm neural network (QPSO-BP) model is proposed. By establishing the three level QPSO-BP mathematical model between GNSS point plane coordinates and normal height, the GNSS elevation transformation is realized. The experimental results show that the method has high global search ability, strong robustness, high fitting and prediction accuracy. This method has good effectiveness and advancement in GNSS elevation transformation.

Key words: quantum particle swarm, BP neural network, GNSS elevation transformation

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