Apply fuzzy clustering optimization algorithm to extracting traffic spatial pattern

Chunchun Hu, Wen Zhong Shi, Lingkui Meng, Min Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Traditional analytical methods for traffic information can't meet to need of intelligent traffic system. Mining value-add information can deal with more traffic problems. The paper exploits a new clustering optimization algorithm to extract useful spatial clustered pattern for predicting long-term traffic flow from macroscopic view. Considering the sensitivity of initial parameters and easy falling into local extreme in FCM algorithm, the new algorithm applies Particle Swarm Optimization method, which can discovery the globe optimal result, to the FCM algorithm. And the algorithm exploits the union of the clustering validity index and objective function of the FCM algorithm as the fitness function of the PSO algorithm. The experimental result indicates that it is effective and efficient. For fuzzy clustering of road traffic data, it can produce useful spatial clustered pattern. And the clustered centers represent the locations which have heavy traffic flow. Moreover, the parameters of the patterns can provide intelligent traffic system with assistant decision support.
Original languageEnglish
Title of host publicationInternational Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Volume7492
DOIs
Publication statusPublished - 23 Nov 2009
EventInternational Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining - Wuhan, China
Duration: 13 Oct 200914 Oct 2009

Conference

ConferenceInternational Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Country/TerritoryChina
CityWuhan
Period13/10/0914/10/09

Keywords

  • FCM
  • PSO
  • Spatial pattern
  • Traffic flow

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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