土壤物理特性的遥感和人工神经网络估计模型

土壤物理特性的遥感和人工神经网络估计模型

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Contributor(s)

Initial contribute: 2018-12-04

Authorship

:  
岳天祥编著
:  
yue@lreis.ac.cn
:  
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Method-focused categoriesData-perspectiveGeostatistical analysis
Method-focused categoriesProcess-perspectivePhysical process calculation

Detailed Description

Chinese {{currentDetailLanguage}} Chinese

土壤物理特性的遥感和人工神经网络估计模型

 

(1)    对一个给定的深度,土壤表层水分与时间的关系为:

式中,分别是饱和水分含量、饱和水力学导度和纹理参数。

(2)    多层前向反馈神经网络的使用:

前向反馈神经网络(FFNN)由三层神经元组成,隐含层中神经元的输出为:

式中,

输出层的结果为:

式中,是一个阶矩阵,表示隐含层中的权;是一个阶矩阵,表示输出层中的权。

 

参考文献:

ChangD HIslamS:利用遥感和人工神经网络估计土壤物理特性。Remote Sensing of Environment2000,74

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《资源环境数学模型手册》 (2018). 土壤物理特性的遥感和人工神经网络估计模型, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/9dfe426b-80ca-483e-a4fb-3faf928d8544
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Last modifier
Mingyuan Li
Last modify time
2020-12-21
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Contributor(s)

Initial contribute : 2018-12-04

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Authorship

:  
岳天祥编著
:  
yue@lreis.ac.cn
:  
View
Is authorship not correct? Feed back

History

Last modifier
Mingyuan Li
Last modify time
2020-12-21
Modify times
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