Machine state classification of electric track circuit by means of logistic regression
Electric track circuits are widely used on railways as sensors providing position of a train and information about physical integrity of rails. A modern railway monitoring system is required to have automatic data analysis capabilities. For a track circuit this functionality can be implemented a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Omsk State Technical University, Federal State Autonoumos Educational Institution of Higher Education
2018-09-01
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| Series: | Омский научный вестник |
| Subjects: | |
| Online Access: | https://www.omgtu.ru/general_information/media_omgtu/journal_of_omsk_research_journal/files/arhiv/2018/4%20(160)/67-72%20%D0%91%D0%BE%D1%80%D0%B8%D1%81%D0%B5%D0%BD%D0%BA%D0%BE%20%D0%94.%20%D0%92.,%20%D0%9F%D1%80%D0%B8%D1%81%D1%83%D1%85%D0%B8%D0%BD%D0%B0%20%D0%98.%20%D0%92.,%20%D0%9B%D1%83%D0%BD%D1%91%D0%B2%20%D0%A1.%20%D0%90..pdf |
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| Summary: | Electric track circuits are widely used on railways as sensors
providing position of a train and information about physical
integrity of rails. A modern railway monitoring system is required
to have automatic data analysis capabilities. For a track circuit this
functionality can be implemented as automatic state classification.
To perform this task, we developed an algorithm based on logistic
regression. In this article we describe basic principles of the
algorithm and machine learning techniques that are applied. |
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| ISSN: | 1813-8225 2541-7541 |