Solar wind data analysis using self-organizing hierarchical neural network classifiers

S. A. Dolenko; Y. V. Orlov; I. G. Persiantsev; J. S. Shugai; A. V. Dmitriev; A. V. Suvorova; I. S. Veselovsky

doi:10.1007/3-540-48219-9_29

Solar wind data analysis using self-organizing hierarchical neural network classifiers

S. A. Dolenko, Y. V. Orlov, I. G. Persiantsev, J. S. Shugai, A. V. Dmitriev, A. V. Suvorova, I. S. Veselovsky

Department of Space Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Recently, we have proposed an algorithm for construction of a hierarchy of neural network classifiers based on a modification of error backpropagation. It combines supervised learning with self-organization. Recursive use of the algorithm results in creation of compact and computationally effective self-organized structures of neural classifiers. The algorithm is applicable for unsupervised analysis of both static objects and dynamic objects, described by time series. In the latter case, the algorithm performs segmentation of the analyzed time-series into parts characterized by different types of dynamics. The algorithm has been successfully tested on pseudo-chaotic maps. In this paper the above algorithm is applied to Solar wind data analysis. Preliminary results indicate that new structural classes in the Solar wind could be distinguished aside from the traditional two- and three-state concepts.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Josef Kittler, Fabio Roli
Publisher	Springer Verlag
Pages	289-298
Number of pages	10
ISBN (Print)	3540422846, 9783540422846
DOIs	https://doi.org/10.1007/3-540-48219-9_29
State	Published - 2001
Event	2nd International Workshop on Multiple Classifier Systems, MCS 2001 - Cambridge, United Kingdom Duration: 2 Jul 2001 → 4 Jul 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2096
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Workshop on Multiple Classifier Systems, MCS 2001
Country/Territory	United Kingdom
City	Cambridge
Period	2/07/01 → 4/07/01

Access to Document

10.1007/3-540-48219-9_29

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Dolenko, S. A., Orlov, Y. V., Persiantsev, I. G., Shugai, J. S., Dmitriev, A. V., Suvorova, A. V., & Veselovsky, I. S. (2001). Solar wind data analysis using self-organizing hierarchical neural network classifiers. In J. Kittler, & F. Roli (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 289-298). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2096). Springer Verlag. https://doi.org/10.1007/3-540-48219-9_29

Dolenko, S. A. ; Orlov, Y. V. ; Persiantsev, I. G. et al. / Solar wind data analysis using self-organizing hierarchical neural network classifiers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Josef Kittler ; Fabio Roli. Springer Verlag, 2001. pp. 289-298 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Dolenko, SA, Orlov, YV, Persiantsev, IG, Shugai, JS, Dmitriev, AV, Suvorova, AV & Veselovsky, IS 2001, Solar wind data analysis using self-organizing hierarchical neural network classifiers. in J Kittler & F Roli (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2096, Springer Verlag, pp. 289-298, 2nd International Workshop on Multiple Classifier Systems, MCS 2001, Cambridge, United Kingdom, 2/07/01. https://doi.org/10.1007/3-540-48219-9_29

Solar wind data analysis using self-organizing hierarchical neural network classifiers. / Dolenko, S. A.; Orlov, Y. V.; Persiantsev, I. G. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Josef Kittler; Fabio Roli. Springer Verlag, 2001. p. 289-298 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2096).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Dolenko SA, Orlov YV, Persiantsev IG, Shugai JS, Dmitriev AV, Suvorova AV et al. Solar wind data analysis using self-organizing hierarchical neural network classifiers. In Kittler J, Roli F, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2001. p. 289-298. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-48219-9_29

Solar wind data analysis using self-organizing hierarchical neural network classifiers

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