Automatic solar flare detection using neural network techniques

We present a new method for automatic detection of flare events from images in the optical range. The method uses neural networks for pattern recognition and is conceived to be applied to full-disk Hα images. Images are analyzed in real time, which allows for the design of automatic patrol processes...

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Autores principales:	Fernandez Borda, R.A., Mininni, P.D., Mandrini, C.H., Gómez, D.O., Bauer, O.H., Rovira, M.G.
Formato:	JOUR
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_00380938_v206_n2_p347_FernandezBorda
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_00380938_v206_n2_p347_FernandezBorda
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spelling	todo:paper_00380938_v206_n2_p347_FernandezBorda2023-10-03T14:48:31Z Automatic solar flare detection using neural network techniques Fernandez Borda, R.A. Mininni, P.D. Mandrini, C.H. Gómez, D.O. Bauer, O.H. Rovira, M.G. We present a new method for automatic detection of flare events from images in the optical range. The method uses neural networks for pattern recognition and is conceived to be applied to full-disk Hα images. Images are analyzed in real time, which allows for the design of automatic patrol processes able to detect and record flare events with the best time resolution available without human assistance. We use a neural network consisting of two layers, a hidden layer of nonlinear neurodes and an output layer of one linear neurode. The network was trained using a back-propagation algorithm and a set of full-disk solar images obtained by HASTA (Hα Solar Telescope for Argentina), which is located at the Estación de Altura Ulrico Cesco of OAFA (Observatorio Astronómico Félix Aguilar), El Leoncito, San Juan, Argentina. This method is appropriate for the detection of solar flares in the complete optical classification, being portable to any Hα instrument and providing unique criteria for flare detection independent of the observer. Fil:Fernandez Borda, R.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mininni, P.D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mandrini, C.H. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Gómez, D.O. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Rovira, M.G. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_00380938_v206_n2_p347_FernandezBorda
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
description	We present a new method for automatic detection of flare events from images in the optical range. The method uses neural networks for pattern recognition and is conceived to be applied to full-disk Hα images. Images are analyzed in real time, which allows for the design of automatic patrol processes able to detect and record flare events with the best time resolution available without human assistance. We use a neural network consisting of two layers, a hidden layer of nonlinear neurodes and an output layer of one linear neurode. The network was trained using a back-propagation algorithm and a set of full-disk solar images obtained by HASTA (Hα Solar Telescope for Argentina), which is located at the Estación de Altura Ulrico Cesco of OAFA (Observatorio Astronómico Félix Aguilar), El Leoncito, San Juan, Argentina. This method is appropriate for the detection of solar flares in the complete optical classification, being portable to any Hα instrument and providing unique criteria for flare detection independent of the observer.
format	JOUR
author	Fernandez Borda, R.A. Mininni, P.D. Mandrini, C.H. Gómez, D.O. Bauer, O.H. Rovira, M.G.
spellingShingle	Fernandez Borda, R.A. Mininni, P.D. Mandrini, C.H. Gómez, D.O. Bauer, O.H. Rovira, M.G. Automatic solar flare detection using neural network techniques
author_facet	Fernandez Borda, R.A. Mininni, P.D. Mandrini, C.H. Gómez, D.O. Bauer, O.H. Rovira, M.G.
author_sort	Fernandez Borda, R.A.
title	Automatic solar flare detection using neural network techniques
title_short	Automatic solar flare detection using neural network techniques
title_full	Automatic solar flare detection using neural network techniques
title_fullStr	Automatic solar flare detection using neural network techniques
title_full_unstemmed	Automatic solar flare detection using neural network techniques
title_sort	automatic solar flare detection using neural network techniques
url	http://hdl.handle.net/20.500.12110/paper_00380938_v206_n2_p347_FernandezBorda
work_keys_str_mv	AT fernandezbordara automaticsolarflaredetectionusingneuralnetworktechniques AT mininnipd automaticsolarflaredetectionusingneuralnetworktechniques AT mandrinich automaticsolarflaredetectionusingneuralnetworktechniques AT gomezdo automaticsolarflaredetectionusingneuralnetworktechniques AT baueroh automaticsolarflaredetectionusingneuralnetworktechniques AT roviramg automaticsolarflaredetectionusingneuralnetworktechniques
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Automatic solar flare detection using neural network techniques

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