An exploratory study and application of data mining: Railway alarm data

Yichuan Yang; Hanning Yuan; Dapeng Li; Tianyun Shi; Wen Cheng

doi:10.1007/978-981-13-0896-3_17

An exploratory study and application of data mining: Railway alarm data

Yichuan Yang, Hanning Yuan^*, Dapeng Li, Tianyun Shi, Wen Cheng

^*Corresponding author for this work

School of Computer Science and Technology

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

Abstract

The railway industry generates large data but there are few researches on railway data analysis. The paper presented an exploratory study and application of data mining from railway alarm data. The railway alarm data is analyzed to find the correlation between alarm items and between railway bureaus when alarm occurred and predict the alarm occurring. The paper proposed an alternative measurement mode with three values: support, Kulc and balance to mine the correlation from alarm data analysis, and the results finally indicated the very possibility of associated railway bureaus.

Original language	English
Title of host publication	Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers
Editors	Hanning Yuan, Jing Geng, Chuanlu Liu, Tisinee Surapunt, Fuling Bian
Publisher	Springer Verlag
Pages	161-169
Number of pages	9
ISBN (Print)	9789811308956
DOIs	https://doi.org/10.1007/978-981-13-0896-3_17
Publication status	Published - 2018
Event	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 - Chiang Mai, Thailand Duration: 8 Dec 2017 → 10 Dec 2017

Publication series

Name	Communications in Computer and Information Science
Volume	849
ISSN (Print)	1865-0929

Conference

Conference	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017
Country/Territory	Thailand
City	Chiang Mai
Period	8/12/17 → 10/12/17

Keywords

Association rules
Data mining
Railway alarm data

Access to Document

10.1007/978-981-13-0896-3_17

Cite this

Yang, Y., Yuan, H., Li, D., Shi, T., & Cheng, W. (2018). An exploratory study and application of data mining: Railway alarm data. In H. Yuan, J. Geng, C. Liu, T. Surapunt, & F. Bian (Eds.), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers (pp. 161-169). (Communications in Computer and Information Science; Vol. 849). Springer Verlag. https://doi.org/10.1007/978-981-13-0896-3_17

Yang, Yichuan ; Yuan, Hanning ; Li, Dapeng et al. / An exploratory study and application of data mining : Railway alarm data. Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. editor / Hanning Yuan ; Jing Geng ; Chuanlu Liu ; Tisinee Surapunt ; Fuling Bian. Springer Verlag, 2018. pp. 161-169 (Communications in Computer and Information Science).

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title = "An exploratory study and application of data mining: Railway alarm data",

abstract = "The railway industry generates large data but there are few researches on railway data analysis. The paper presented an exploratory study and application of data mining from railway alarm data. The railway alarm data is analyzed to find the correlation between alarm items and between railway bureaus when alarm occurred and predict the alarm occurring. The paper proposed an alternative measurement mode with three values: support, Kulc and balance to mine the correlation from alarm data analysis, and the results finally indicated the very possibility of associated railway bureaus.",

keywords = "Association rules, Data mining, Railway alarm data",

author = "Yichuan Yang and Hanning Yuan and Dapeng Li and Tianyun Shi and Wen Cheng",

note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2018.; 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 ; Conference date: 08-12-2017 Through 10-12-2017",

year = "2018",

doi = "10.1007/978-981-13-0896-3_17",

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Yang, Y, Yuan, H, Li, D, Shi, T & Cheng, W 2018, An exploratory study and application of data mining: Railway alarm data. in H Yuan, J Geng, C Liu, T Surapunt & F Bian (eds), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Communications in Computer and Information Science, vol. 849, Springer Verlag, pp. 161-169, 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017, Chiang Mai, Thailand, 8/12/17. https://doi.org/10.1007/978-981-13-0896-3_17

An exploratory study and application of data mining: Railway alarm data. / Yang, Yichuan; Yuan, Hanning; Li, Dapeng et al.
Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. ed. / Hanning Yuan; Jing Geng; Chuanlu Liu; Tisinee Surapunt; Fuling Bian. Springer Verlag, 2018. p. 161-169 (Communications in Computer and Information Science; Vol. 849).

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

TY - GEN

T1 - An exploratory study and application of data mining

T2 - 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

AU - Yang, Yichuan

AU - Yuan, Hanning

AU - Li, Dapeng

AU - Shi, Tianyun

AU - Cheng, Wen

N1 - Publisher Copyright: © Springer Nature Singapore Pte Ltd. 2018.

PY - 2018

Y1 - 2018

N2 - The railway industry generates large data but there are few researches on railway data analysis. The paper presented an exploratory study and application of data mining from railway alarm data. The railway alarm data is analyzed to find the correlation between alarm items and between railway bureaus when alarm occurred and predict the alarm occurring. The paper proposed an alternative measurement mode with three values: support, Kulc and balance to mine the correlation from alarm data analysis, and the results finally indicated the very possibility of associated railway bureaus.

AB - The railway industry generates large data but there are few researches on railway data analysis. The paper presented an exploratory study and application of data mining from railway alarm data. The railway alarm data is analyzed to find the correlation between alarm items and between railway bureaus when alarm occurred and predict the alarm occurring. The paper proposed an alternative measurement mode with three values: support, Kulc and balance to mine the correlation from alarm data analysis, and the results finally indicated the very possibility of associated railway bureaus.

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KW - Data mining

KW - Railway alarm data

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BT - Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers

A2 - Yuan, Hanning

A2 - Geng, Jing

A2 - Liu, Chuanlu

A2 - Surapunt, Tisinee

A2 - Bian, Fuling

PB - Springer Verlag

Y2 - 8 December 2017 through 10 December 2017

ER -

Yang Y, Yuan H, Li D, Shi T, Cheng W. An exploratory study and application of data mining: Railway alarm data. In Yuan H, Geng J, Liu C, Surapunt T, Bian F, editors, Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Springer Verlag. 2018. p. 161-169. (Communications in Computer and Information Science). doi: 10.1007/978-981-13-0896-3_17

An exploratory study and application of data mining: Railway alarm data

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