Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina Desenvolvimento e avaliação de modelos de redes neurais para estimação da irradiação solar diária em Córdoba, Argentina

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.<br>O objetivo deste trabalho foi desenvolver modelos de redes neuronais, do tipo retropropagação, para a estimação da irradiação solar, a partir de dados de irradiação solar extraterrestre, amplitude térmica, precipitação, nebulosidade e razão de insolação. O treinamento e a validação foram realizados com dados correspondentes a Córdoba, Argentina. O comportamento e ajuste entre os valores observados e os estimados pelas redes foram avaliados para diferentes combinações das variáveis de entrada, que apresentaram valores do erro quadrático médio entre 3,15 e 3,88 MJ m-2 d-1 . Este último valor corresponde ao modelo que calcula a irradiação somente utilizando precipitação e amplitude térmica diária. Os resultados exibem em todos os modelos um ajuste apropriado ao comportamento sazonal da irradiação solar e permitem concluir a pertinência e o adequado desempenho desse método para estimar fenômenos complexos como a irradiação solar

Electronic and optical properties of the H 2O adsorbed the B-N-C nanotubes

We investigate the structures and properties of boron/nitrogen co-doped carbon nanotube with water molecules adsorbing. The electronic and optical properties of the systems are calculated by using the first-principles theory in detail. The results reveal that the doped nanotubes show hydrophilic behavior when the oxygen atoms are close to the nanotubes. The Mulliken charges redistribute and transfer between the doped carbon nanotubes and the water molecules. The band gaps of the nanotubes vary with the positions of H2O. The positions and intensities of the reflectivity peaks are affected by the distributions of boron/nitrogen atoms and the positions of water molecules. The investigations are beneficial to further biological applications of co-doped nanotubes