An Expressway Congestion Detection Algorithm Based on ETC Data Mining - Details

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Traffic　congestion　is　the　most　widespread　and　influential　problem　among　all　the　traffic　problems.　The　key　to　solve　this　problem　is　the　discrimination　and　analysis　of　traffic　congestion.　In　order　to　provide　more　accurate　and　comprehensive　information　on　the　changes　of　traffic　conditions,　we　propose　a　new　method　of　processing　ETC　data　and　a　new　expressway　congestion　detection　algorithm　combining　processed　ETC　trade　data　and　weighted-FCM　algorithm　aiming　to　enhance　monitoring　the　status　of　expressway.　©　2022,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd.

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Data handling Data mining Intelligent systems Signal detection Traffic congestion

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[ 1 ] [Yu, Xiang]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China
[ 2 ] [Zou, FuMin]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China
[ 3 ] [Guo, Feng]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China
[ 4 ] [Guo, Feng]FuZhou University, FuZhou; 350108, China
[ 5 ] [Gu, Qing]Fujian Provincial Expressway Information Technology Co., Ltd., FuZhou; 350011, China
[ 6 ] [Chen, ZiYu]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China
[ 7 ] [Luo, YongYu]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China
[ 8 ] [Chen, HaoBin]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, FuZhou; 350108, China

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ISSN： 2190-3018

Year： 2022

Volume： 277

Page： 269-279

Language： English

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SCOPUS Cited Count： 2

ESI Highly Cited Papers on the List： 0 Unfold All

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