Sunspot group classification method based on deep learning

A technology of sunspots and deep learning, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve problems such as different precision, reduce the probability of misclassification, and improve the effect of classification accuracy

Inactive Publication Date: 2021-06-11
BEIHANG UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, in the method of classifying sunspot groups using deep learning, one type of observation image is used to train the model to realize the prediction of sunspot group, but different types of obser...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Sunspot group classification method based on deep learning
  • Sunspot group classification method based on deep learning
  • Sunspot group classification method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be pointed out that the described embodiments are only intended to facilitate understanding of the present invention and do not serve as any limitation.

[0052] The invention provides a method for classifying sunspot groups based on deep learning. The classification method uses two images of sunspot group magnetic field observation and white light observation, and uses a deep learning network to process the two images respectively. According to the deep learning model The training accuracy gives a certain weight to the prediction results of the two images, and obtains the comprehensive prediction results of the two images of the same sunspot group. Compared with the existing sunspot group classification method, this method uses two observation images of the sunspot group to predict the same target through the deep learning network, and ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a sunspot group classification method based on deep learning. The classification method comprises the following steps: observing two images by using a sunspot group magnetic field and white light, and respectively processing the two images by using a deep learning network; performing certain weight processing on the prediction results of the two images according to the training precision of the deep learning model to obtain a comprehensive prediction result of the two images of the same sunspot group. Compared with an existing sunspot group classification method, the method utilizes two observation images of the sunspot group, predicts the same target through the deep learning network, comprehensively evaluates the predicted target according to the training precision of the two images, weights the prediction confidence, and further improves the classification precision of the sunspot group.

Description

technical field [0001] The invention relates to a method for classifying sunspot groups based on deep learning, and belongs to the technical fields of image processing and astronomy. Background technique [0002] The area where the magnetic field gathers on the surface of the sun’s photosphere is called sunspots, and when sunspots appear in groups in local areas, it is called sunspot groups. The appearance of sunspot groups is often associated with solar activities, and the appearance of some sunspot groups during solar activities, such as flares, will have a serious impact on the earth, disrupt the earth's ionosphere, generate magnetic storms, and disrupt wireless communications. Deep learning is a field of machine learning that has developed rapidly in recent years. Its concept comes from artificial neural networks, including multi-layer perceptrons with multiple hidden layers. The basic feature is to imitate the transmission between neurons in the brain, and the mode of ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/08G06F18/24
Inventor 刘杨宾学恒
Owner BEIHANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products