Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina

Pesquisa Agropecuária Brasileira

Mónica Bocco¹  Gustavo Ovando¹  Silvina Sayago¹ 

[1] ,Universidad Nacional de Córdoba Facultad de Ciencias Agropecuarias Córdoba,Argentina

关键词: modelling;    prediction;    backpropagation neural networks;    modelagem;    predição;    redes neurais de retropropagação;   

DOI  :  10.1590/S0100-204X2006000200001

来源: SciELO

【 摘 要 】

The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m-2 d-1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation.

【 授权许可】

CC BY   
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