李冲, 李建成, 黄瑞金, 谭理. 考虑欧拉矢量的BP神经网络模型建立区域地壳运动速率场[J]. 武汉大学学报 ( 信息科学版), 2014, 39(3): 362-366. DOI: 10.13203/j.whugis20120046
引用本文: 李冲, 李建成, 黄瑞金, 谭理. 考虑欧拉矢量的BP神经网络模型建立区域地壳运动速率场[J]. 武汉大学学报 ( 信息科学版), 2014, 39(3): 362-366. DOI: 10.13203/j.whugis20120046
LI Chong, LI Jiancheng, HUANG Ruijin, TAN Li. Building up Regional Crustal Movement Velocity Field with BPNeural Network Base on Euler Vector[J]. Geomatics and Information Science of Wuhan University, 2014, 39(3): 362-366. DOI: 10.13203/j.whugis20120046
Citation: LI Chong, LI Jiancheng, HUANG Ruijin, TAN Li. Building up Regional Crustal Movement Velocity Field with BPNeural Network Base on Euler Vector[J]. Geomatics and Information Science of Wuhan University, 2014, 39(3): 362-366. DOI: 10.13203/j.whugis20120046

考虑欧拉矢量的BP神经网络模型建立区域地壳运动速率场

Building up Regional Crustal Movement Velocity Field with BPNeural Network Base on Euler Vector

  • 摘要: 目的 讨论了常用的欧拉矢量模型和函数拟合模型的优缺点,提出了基于欧拉矢量的BP神经网络模型。该模型运用欧拉矢量的地学性质,结合 BP神经网络在处理需要同时考虑许多因素和条件的、不确定和模糊的信息时的优势,可以较好地区分块体整体的刚性旋转及内部的弹性形变。经实例验证,取得较好的精度。

     

    Abstract: Objective In regional crustal movement research,mathematical model is always used to estimate with-out observation the points which need attention.Then,we can build up a relatively even and meaning-ful regional crustal movement velocity field.In this paper we analyze the strengths and weaknesses ofthe common Euler and function models,and propose a new model with BP neural network based onEuler vector.This proposed model uses the geological properties of a Euler vector and the superiorityof BP neural network.It considers the various influences and uncertain information found in data pro-cessing.Therefore,the model can distinguish inner elastic strain from rigid-body of the plate.Theproposed model obtains precision through specimen verification.

     

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