Zusammenfassung
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.
Nutzer