Data Mining Improves Pipeline Risk Assessment
- 10.2991/iccsee.2013.668How to use a DOI?
- risk assessment, data mining, pipeline risk
Accidents to pipelines have been recorded and they often result in catastrophic consequences for environment and society with a great deal of economic loss. Standard methods of evaluating pipeline risk have stressed index-based and conditional based data assessment processes. Data mining represents a shift from verification-driven data analysis approaches to discovery-driven methods in risk assessment.
- © 2013, 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/).
Cite this article
TY - CONF AU - Baoqin Wang AU - Xuyang Zhou AU - Wenjing Zhang PY - 2013/03 DA - 2013/03 TI - Data Mining Improves Pipeline Risk Assessment BT - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) PB - Atlantis Press SP - 2683 EP - 2686 SN - 1951-6851 UR - https://doi.org/10.2991/iccsee.2013.668 DO - 10.2991/iccsee.2013.668 ID - Wang2013/03 ER -