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

^*此作品的通讯作者

Beijing Institute of Technology
CAS - Institute of Computing Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

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.

源语言	英语
主期刊名	Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers
编辑	Hanning Yuan, Jing Geng, Chuanlu Liu, Tisinee Surapunt, Fuling Bian
出版商	Springer Verlag
页	161-169
页数	9
ISBN（印刷版）	9789811308956
DOI	https://doi.org/10.1007/978-981-13-0896-3_17
出版状态	已出版 - 2018
已对外发布	是
活动	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 - Chiang Mai, 泰国期限: 8 12月 2017 → 10 12月 2017

出版系列

姓名	Communications in Computer and Information Science
卷	849
ISSN（印刷版）	1865-0929

会议

会议	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017
国家/地区	泰国
市	Chiang Mai
时期	8/12/17 → 10/12/17

访问文件

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

其它文件与链接

链接到 Scopus 的出版物

引用此

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

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

@inproceedings{ade99c1c4c4b4788b987c6bd22259784,

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",

language = "English",

isbn = "9789811308956",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "161--169",

editor = "Hanning Yuan and Jing Geng and Chuanlu Liu and Tisinee Surapunt and Fuling Bian",

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

address = "Germany",

}

Yang, Y, Yuan, H, Li, D, Shi, T & Cheng, W 2018, An exploratory study and application of data mining: Railway alarm data. 在 H Yuan, J Geng, C Liu, T Surapunt & F Bian (编辑), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Communications in Computer and Information Science, 卷 849, Springer Verlag, 页码 161-169, 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017, Chiang Mai, 泰国, 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 等.
Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. 编辑 / Hanning Yuan; Jing Geng; Chuanlu Liu; Tisinee Surapunt; Fuling Bian. Springer Verlag, 2018. 页码 161-169 (Communications in Computer and Information Science; 卷 849).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

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.

KW - Association rules

KW - Data mining

KW - Railway alarm data

UR - https://www.scopus.com/pages/publications/85049025062

U2 - 10.1007/978-981-13-0896-3_17

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

M3 - Conference contribution

AN - SCOPUS:85049025062

SN - 9789811308956

T3 - Communications in Computer and Information Science

SP - 161

EP - 169

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. 在 Yuan H, Geng J, Liu C, Surapunt T, Bian F, 编辑, Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Springer Verlag. 2018. 页码 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

摘要

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会议

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