Detail publikace

MACHINE LEARNING BASED TRAIN TYPE IDENTIFICATION AT RAILROAD SWITCH USING VIBRATION

KRATOCHVÍLOVÁ, M.

Originální název

MACHINE LEARNING BASED TRAIN TYPE IDENTIFICATION AT RAILROAD SWITCH USING VIBRATION

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This work concerns the use of machine learning to identify trains passing through S&C based on the acceleration signal measured in the track. This system can be use in the future, for example, to track changes in the stiffness of the bearing structure over time and thus predict the need for maintenance. Several methods of machine learning were compared based on their accuracy, time and computational demands for a given problem and the optimal method (Support Vector Machine) was implemented on real data. Because of the small amount of usable data, the bootstrapping method was used to generate training and test datasubsets.

Klíčová slova

Machine learning, switches and crossings, acceleration, train, support vector machine

Autoři

KRATOCHVÍLOVÁ, M.

Vydáno

23. 1. 2020

Nakladatel

Econ Publishing s.r.o.

Místo

Brno

ISBN

978-80-86433-73-8

Kniha

22. ODBORNÁ KONFERENCE DOKTORSKÉHO STUDIA

Edice

22

Strany od

211

Strany do

216

Strany počet

937

URL

http://www.juniorstav.cz/wp-content/uploads/2020/02/Sbornik_Komplet_FINAL-uprava.pdf

BibTex

@inproceedings{BUT162430,
  author="Martina {Pálková}",
  title="MACHINE LEARNING BASED TRAIN TYPE IDENTIFICATION AT RAILROAD SWITCH USING VIBRATION",
  booktitle="22. ODBORNÁ KONFERENCE DOKTORSKÉHO STUDIA",
  year="2020",
  series="22",
  pages="211--216",
  publisher="Econ Publishing s.r.o.",
  address="Brno",
  isbn="978-80-86433-73-8",
  url="http://www.juniorstav.cz/wp-content/uploads/2020/02/Sbornik_Komplet_FINAL-uprava.pdf"
}