Application of machine learning methods to the solar disk state detection by all-sky images over the ocean

Abstract

A new approach to automatic solar disk state detection by all-sky images using machine learning methods is developed and implemented. The efficiency of the most widely used machine learning algorithms is analyzed. The effect of reducing the dimensionality of the feature space on the classification accuracy is estimated. The multilayer artificial neural network model has shown the best accuracy in terms of the true score. The operation result demonstrates the effectiveness of machine learning methods applied to solar disk state detection by all-sky images.