Research on Earning Warning of Railway Freight Based on Support Vector Regression (SVR)

DOI

10.2991/icmmcce-15.2015.504How to use a DOI?

Keywords

Earning Warning, Railway Freight, SVR

Abstract

The traditional railway freight early warning adopted independent indicator thresholds discrimination. But it would lead to inaccurate results warnings, it may alarms when abnormal events occur instead of early warning. This paper proposes a railway freight early warning model, which apply support vector regression (SVR) to rail freight early warning. this model could find their variation, sum up the formation of abnormal alarm mod by analyzing historical indicators, including of number of booking railway freight vehicles, loading vehicles, freight volume and freight turnover quantity. Early warning signals will be given when an exception occurs at the beginning of freight. Early analysis and processing potential risk are as to stabilize railway freight market. Experimental result shows a high prediction accuracy of this model for the railway freight market.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lingyan Cheng
AU  - Shiwei He
AU  - Weichuan Yin
PY  - 2015/12
DA  - 2015/12
TI  - Research on Earning Warning of Railway Freight Based on Support Vector Regression (SVR)
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.504
DO  - 10.2991/icmmcce-15.2015.504
ID  - Cheng2015/12
ER  -