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JOURNALS // Computer Optics // Archive

Computer Optics, 2022 Volume 46, Issue 3, Pages 506–512 (Mi co1040)

This article is cited in 17 papers

NUMERICAL METHODS AND DATA ANALYSIS

A method for analyzing complex structured data with elements of machine learning

B. S. Mandrikova

Institute of Cosmophysical Researches and Radio Wave Propagation, Far East Division, Russian Academy of Sciences

Abstract: A method for analyzing data of complex structure based on combining a wavelet transform and neural networks Autoencoder is proposed. The method allows you to research the data structure, detect abnormal changes of various shapes and durations, and suppress noise. The efficiency of the method is shown on the example of data from a network of neutron monitor stations. Neutron monitor data determine the intensity of secondary cosmic rays and are one of the key factors in space weather. The numerical implementation of the method allows it to be applied on-line, which is of interest in problems of analyzing environmental data and detecting catastrophic events.

Keywords: data analysis, data of complex structure, wavelet transform, neural networks, neutron monitors

Received: 19.12.2021
Accepted: 06.02.2022

DOI: 10.18287/2412-6179-CO-1088



© Steklov Math. Inst. of RAS, 2024