KFU. Card publication. A classification of meteor radio echoes based on artificial neural network

KAZAN
FEDERAL UNIVERSITY

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A CLASSIFICATION OF METEOR RADIO ECHOES BASED ON ARTIFICIAL NEURAL NETWORK

Form of presentation

Articles in international journals and collections

Year of publication

2018

Authors, employees of KFU

Karpov Arkadiy Vasilevich, author

Authors, postgraduates KFU

Danilov Mikhail Valeryanovich, postgraduate kfu

Bibliographic description in the original language

Danilov, M. & Karpov, A. (2018). A classification of meteor radio echoes based on artificial neural network. Open Astronomy, 27(1), pp. 318-325. Retrieved 19 Dec. 2018, from doi:10.1515/astro-2018-0037

Annotation

Open Astronomy

Keywords

Meteor radio echoes, Classification algorithms, Artificial neural networks, Radiowave propagation

Place of publication

Варшава

The name of the journal

Open Astronomy

Publishing house

DE GRUYTER Poland

URL

https://doi.org/10.1515/astro-2018-0037

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=192416&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Karpov Arkadiy Vasilevich	ru_RU
dc.contributor.author	Danilov Mikhail Valeryanovich	ru_RU
dc.date.accessioned	2018-01-01T00:00:00Z	ru_RU
dc.date.available	2018-01-01T00:00:00Z	ru_RU
dc.date.issued	2018	ru_RU
dc.identifier.citation	Danilov, M. & Karpov, A. (2018). A classification of meteor radio echoes based on artificial neural network. Open Astronomy, 27(1), pp. 318-325. Retrieved 19 Dec. 2018, from doi:10.1515/astro-2018-0037	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=192416&p_lang=2	ru_RU
dc.description.abstract	Open Astronomy	ru_RU
dc.description.abstract	An artificial neural network is described for classification of meteor trails into the distinct overdense, intermediate and underdense trail categories. The neural network was trained and on model data obtained using the ?KAMET? program and tested on real data. The best result of classification success rate of 95% without according to the heights of the formation of meteor trails. Results of classification with according to the heights of the formation of meteor trails are 82% - 91%.	ru_RU
dc.language.iso	ru	ru_RU
dc.publisher	DE GRUYTER Poland	ru_RU
dc.subject	Meteor radio echoes	ru_RU
dc.subject	Classification algorithms	ru_RU
dc.subject	Artificial neural networks	ru_RU
dc.subject	Radiowave propagation	ru_RU
dc.title	A classification of meteor radio echoes based on artificial neural network	ru_RU
dc.type	Articles in international journals and collections	ru_RU