基于遗传算法与人工神经网络的玉米估产评价模型

基于遗传算法与人工神经网络的玉米估产评价模型

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contributed at 2018-12-04

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

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Chinese {{currentDetailLanguage}} Chinese

基于遗传算法与人工神经网络的玉米估产评价模型

 

选择方式不采用比例选择方式,而使用亲代度量决定群体中每个体被选种的概率,群体中的个体以式(2)所示的概率作为亲代染色体。

式中,分别表示评价函数最优、次优、第三的个体概率。

3BP网络模型:

式中,为输入层节点为输入层到隐含层的连接权重;为隐含层单元的阈值。对于,它们的初值是按概率得到的随机数。激活函数Sigmoid函数:

然后根据式(3)和式(4)计算输出层节点的激活值:

式中,为隐含层到输出层的连接权重;为输出层的阈值;也是按概率确定的随机数。

根据式(6)计算输出层的一般化误差:

式中,为输出层单元的期望输出。

最后计算隐含单元相对于每个的误差:

 

参考文献:

李哲,张军涛:基于遗传算法与人工神经网络相结合的玉米估产研究。自然资源学报,2000,153

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How to Cite

《资源环境数学模型手册》 (2018). 基于遗传算法与人工神经网络的玉米估产评价模型, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/e08038a2-caaf-48e9-9075-fc10d2089411
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Last modifier : 
tingxin
Last modify time : 
2020-10-29
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Contributor(s)

initial contribute: 2018-12-04

Authorship

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

History

Last modifier : 
tingxin
Last modify time : 
2020-10-29
Modify times : 
View History

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