DocumentCode
3160951
Title
Natural gas pipeline leak detection based on data mining
Author
Wang, Xiu-fang ; Wang, Yan ; Jiang, Chun-lei ; Liang, Hong-wei
Author_Institution
Inf. & Commun. Eng. Inst., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2011
fDate
16-18 April 2011
Firstpage
492
Lastpage
494
Abstract
Using data mining´s decision tree classification, DBSCN cluster analysis, and K-nearest neighbor algorithm realizes the information mining of natural gas pipeline leak, and alse uncovers the objective laws behind the natural gas pipeline transmission, intrinsically linking to the each parameter and development trend. We could reduce the risk of accidents and economic losses, in order to control the natural gas transmission in advance.
Keywords
data mining; decision trees; natural gas technology; pattern clustering; pipelines; DBSCN cluster analysis; accident risk; data mining; decision tree classification; economic losses; k-nearest neighbor algorithm; natural gas pipeline leak detection; natural gas transmission; Accidents; Classification algorithms; Data mining; Decision trees; Materials; Natural gas; Pipelines; Data mining; Development trend; Natural gas pipeline leak; Objective law;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location
XianNing
Print_ISBN
978-1-61284-458-9
Type
conf
DOI
10.1109/CECNET.2011.5768886
Filename
5768886
Link To Document