The application of Bayesian network classifiers to cloud classification in satellite images

This adaptation benefits plant performance and allows electricity management to be integrated into the electricity grid. Nonetheless, the majority of cloud studies determine atmospheric parameters, which are sometimes not available. In this work, we have developed an automatic, fully-exportable cloud classification model, where Bayesian network classifiers were applied to satellite images so as to determine the presence of clouds, classifying the sky as cloudless or with high, medium and low cloud presence. There was an average success probability of 90% for all sky conditions.