Распознавание геомагнитных бурь на основе матричных временных рядов наблюдений мюонного годоскопа УРАГАН с использованием нейронных сетей глубокого обучения

Abstract

We solve the problem of recognizing geomagnetic storms from matrix time series of observations with the URAGAN muon hodoscope, using deep learning neural networks. A variant of the neural network software module is selected and its parameters are determined. Geomagnetic storms are recognized using binary classification procedures; a decision-making rule is formed. We estimate probabilities of correct and false recognitions. The recognition of geomagnetic storms is experimentally studied; for the assigned Dst threshold Yᴅ₀=–45 nT we obtain acceptable probabilities of correct and false recognitions, which amount to β=0.8212 and α=0.0047. We confirm the effectiveness and prospects of the proposed neural network approach.