Infrastructure Construction and Data Analysis for Machine Learning Based Automatic Train Operation Scheme 


Vol. 43,  No. 4, pp. 784-789, Apr.  2018
10.7840/kics.2018.43.4.784


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  Abstract

In this paper, we construct an infrastructure and analyze environmental variables affecting to performance of ATO system to development new train operation system applying environmental variables, such as temperature and humidity, and car condition information which is not considered in the existing ATO system. We make a sensor platform to estimate accuracy of stop of trains and analyze data gathered by the sensor platform to extract variables for machine learning.

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  Cite this article

[IEEE Style]

K. Ko and J. Kim, "Infrastructure Construction and Data Analysis for Machine Learning Based Automatic Train Operation Scheme," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 4, pp. 784-789, 2018. DOI: 10.7840/kics.2018.43.4.784.

[ACM Style]

Kyeongjun Ko and Jungtai Kim. 2018. Infrastructure Construction and Data Analysis for Machine Learning Based Automatic Train Operation Scheme. The Journal of Korean Institute of Communications and Information Sciences, 43, 4, (2018), 784-789. DOI: 10.7840/kics.2018.43.4.784.

[KICS Style]

Kyeongjun Ko and Jungtai Kim, "Infrastructure Construction and Data Analysis for Machine Learning Based Automatic Train Operation Scheme," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 4, pp. 784-789, 4. 2018. (https://doi.org/10.7840/kics.2018.43.4.784)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880