scholarly journals Comparison between Random Forests, Artificial Neural Networks and Gradient Boosted Machines Methods of On-Line Vis-NIR Spectroscopy Measurements of Soil Total Nitrogen and Total Carbon

Sensors ◽  
2017 ◽  
Vol 17 (10) ◽  
pp. 2428 ◽  
Author(s):  
Said Nawar ◽  
Abdul Mouazen
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Total Nitrogen ◽  
Random Forests ◽  
Nir Spectroscopy ◽  
Total Carbon ◽  
Soil Total Nitrogen ◽  
On Line ◽  
Artificial Neural

scholarly journals Modelling and Prediction of Monthly Global Irradiation Using Different Prediction Models

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2332
Author(s):  
Cecilia Martinez-Castillo ◽  
Gonzalo Astray ◽  
Juan Carlos Mejuto
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Random Forests ◽  
Prediction Models ◽  
Meteorological Station ◽  
Ann Model ◽  
Global Irradiation ◽  
Artificial Neural ◽  
Input Variables ◽  
Using Data

Different prediction models (multiple linear regression, vector support machines, artificial neural networks and random forests) are applied to model the monthly global irradiation (MGI) from different input variables (latitude, longitude and altitude of meteorological station, month, average temperatures, among others) of different areas of Galicia (Spain). The models were trained, validated and queried using data from three stations, and each best model was checked in two independent stations. The results obtained confirmed that the best methodology is the ANN model which presents the lowest RMSE value in the validation and querying phases 1226 kJ/(m2∙day) and 1136 kJ/(m2∙day), respectively, and predict conveniently for independent stations, 2013 kJ/(m2∙day) and 2094 kJ/(m2∙day), respectively. Given the good results obtained, it is convenient to continue with the design of artificial neural networks applied to the analysis of monthly global irradiation.

On-Line Estimation of Transit Time Using Artificial Neural Networks

1998 ◽  
Vol 130 (1) ◽  
pp. 113-127 ◽  
Author(s):  
T. Tambouratzis ◽  
M. Antonopoulos-Domis ◽  
M. Marseguerra ◽  
E. Padovani
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Transit Time ◽  
On Line ◽  
Artificial Neural
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