Artificial neural network application in comparison with modeling allometric equations for predicting above-ground biomass in the Hyrcanian mixed-beech forests of Iran

2016 ◽  
Vol 88 ◽  
pp. 66-76 ◽  
Author(s):  
Ali Asghar Vahedi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Allometric Equations ◽  
Above Ground Biomass ◽  
Beech Forests ◽  
Ground Biomass ◽  
Network Application ◽  
Artificial Neural

Modeling grassland above-ground biomass based on artificial neural network and remote sensing in the Three-River Headwaters Region

2018 ◽  
Vol 204 ◽  
pp. 448-455 ◽  
Author(s):  
Shuxia Yang ◽  
Qisheng Feng ◽  
Tiangang Liang ◽  
Baokang Liu ◽  
Wenjuan Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Artificial Neural Network ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Artificial Neural

scholarly journals Применение искусственной нейронной сети в экспериментах по ядерному спиновому эху

2019 ◽  
Vol 45 (12) ◽  
pp. 16
Author(s):  
С.Н. Полулях ◽  
А.И. Горбованов
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Nuclear Spin ◽  
Spin Echo ◽  
Gaussian Form ◽  
The Neural Network ◽  
Network Application ◽  
Artificial Neural

The possibility of artificial neural network application to detect nuclear spin echo signals under conditions when the echo amplitude is comparable to the amplitude of the noise is demonstrated. Data obtained by superimposing the model echo signals of a Gaussian form on experimentally recorded noise signals is proposed to use for training the neural network.

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