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
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;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
DOI :
10.1109/CECNET.2011.5768886
