模糊似然度计算模型

模糊似然度计算模型

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Contributor(s)

Initial contribute: 2018-12-04

Authorship

Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
Homepage:  
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Method-focused categoriesData-perspectiveIntelligent computation analysis

Model Description

Chinese {{currentDetailLanguage}} Chinese

模糊似然度计算模型

 

每个组别的模糊似然度可根据组中样本的平均值,最小值,最大值恢复得到,似然度反比于输入矢量与类别平均值的距离,的取值最小为,最大为,模糊组别似然度可给为:

式中,,对

类别选择:对每个输入矢量和结点处,组别选择通过一个判别条件(DC)来控制。只有当最高的模糊似然度超过次高的模糊似然度一个最小的模糊隶属水平,判别条件才作出选择。作为判别条件的最小模糊隶属水平可通过对一个专用的未知类别的似然度的调整而加以设置,如,则:

式中,

 

参考文献:

Abuelgasim ARoss W DGopal S et al:利用自适应模糊神经网络进行变化探测:海湾战争后的环境损害评估。Remote Sensing of Environment1999,70

How to Cite

《资源环境数学模型手册》 (2018). 模糊似然度计算模型, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/85fe0889-a951-49be-9f8f-750300204b44
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Last modifier : 
wzh
Last modify time : 
2020-12-24
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Contributor

Initial contribute: 2018-12-04

Co-contributor(s)

Authorship

Affiliation:  
岳天祥编著
Email:  
yue@lreis.ac.cn
Homepage:  
View
Is authorship not correct? Feedback

History

Last modifier : 
wzh
Last modify time : 
2020-12-24
Modify times : 
View History

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