Data Mining Improves Pipeline Risk Assessment


== Abstract ==

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.


== Original document ==

The different versions of the original document can be found in:

* [http://download.atlantis-press.com/php/download_paper.php?id=5099 http://download.atlantis-press.com/php/download_paper.php?id=5099] under the license cc-by

* [http://dx.doi.org/10.2991/iccsee.2013.668 http://dx.doi.org/10.2991/iccsee.2013.668]

* [http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2168 http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2168]

* [https://www.scientific.net/AMM.347-350.2168 https://www.scientific.net/AMM.347-350.2168],
: [https://www.atlantis-press.com/proceedings/iccsee-13/5099 https://www.atlantis-press.com/proceedings/iccsee-13/5099],
: [https://academic.microsoft.com/#/detail/2001485629 https://academic.microsoft.com/#/detail/2001485629]

* [https://www.scientific.net/AMM.347-350.2168.pdf https://www.scientific.net/AMM.347-350.2168.pdf],
: [http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2168 http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2168]



DOIS: 10.4028/www.scientific.net/amm.347-350.2168 10.2991/iccsee.2013.668