Method for forecasting solar flare outbreak based on 3D convolutional neural network

Abstract

The invention discloses a method for forecasting solar flare outbreak based on a 3D convolutional neural network. The method comprises the following steps: 1, constructing an observation data cube byadopting continuous observation data; 2, training the 3D convolutional neural network model by adopting the training set; and 3, inputting the test set into the trained 3D convolutional neural networkmodel for prediction. According to the method, a series of solar activity area images which are continuous in time are positioned, tracked, intercepted and corrected, so that the problem of image distortion subsequently input into a model can be avoided, and a result is more realistic; and the processed data is matched with a specific 3D convolutional neural network of the method, and time sequence information contained in solar continuous observation data can be fully extracted, so that evolution process information of an activity area is captured, and the accuracy of solar flare forecastingof the model is effectively improved; and meanwhile, due to the fact that continuous sun observation data is used, the complexity of observation data collection and arrangement work is effectively reduced.

Description

technical field [0001] The invention relates to a method for forecasting the outbreak of solar flares based on a 3D convolutional neural network, which belongs to the fields of astronomical technology and image processing. Background technique [0002] With the development of human science and technology, especially the continuous deepening of space exploration and development activities, the impact of space weather on human activities continues to deepen. The solar flare outbreak is an important manifestation of the harsh conditions of space weather. High-intensity solar flares will pose a threat to radio communications, satellite navigation, and even space flight and the safety of astronauts. Therefore, it is of great significance to accurately predict the outbreak of solar flares to avoid or reduce the harm of solar flares to human beings. [0003] Solar flare is a violent eruption phenomenon of the sun, and the research on the prediction of solar flare explosion has alw...

AI Technical Summary

Problems solved by technology

However, the above-mentioned solar flare prediction models based on convolutional neural networks use traditional 2D convolutional neural networks, and their convolution kernels can only be convolved on planar images, that is, two-dimensional data, and cannot make full use of continuous Time Dimension Information Contained in Solar Observation Data

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