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Traffic status evaluation based on fuzzy clustering and RBF neural network

  • Tongji University
  • University of Florida

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

This paper introduces the C-means fuzzy clustering method to evaluate the road traffic status. During the analysis, road traffic status was categorized into four types by using ISODATA algorithm based on expert knowledge. Meanwhile, RBF neural network classification model was established to evaluate the road traffic status. The implementation results showed that the proposed method was capable of evaluating road traffic status, and reflecting the related quantitative fluctuations.

Original languageEnglish
Title of host publicationProceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
Pages1405-1408
Number of pages4
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010 - Yantai, Shandong, China
Duration: 10 Aug 201012 Aug 2010

Publication series

NameProceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
Volume3

Conference

Conference2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
Country/TerritoryChina
CityYantai, Shandong
Period10/08/1012/08/10

Keywords

  • Fuzzy C-means clustering
  • ISODATA algorithm
  • RBF neural network
  • Road traffic status evaluation
  • Traffic congestion

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