Fuzzy learning classifier system and its application research in automatic traffic incident detection

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

Abstract

According to the application of pattern classification, a fuzzy learning classifier system was described in detail, including its framework and each important module. Furthermore, the paper also designed the classifier encoding, fitness parameter definition, etc. Then this system was applied in automatic traffic incident detection using 1-880 field data and compared with BP Network on the detection performance. The BP Network was improved with Levenberg-Marquardt method. The comparison result showed that the fuzzy learning classifier system designed in this paper had lower false detection rate and shorter detection time, which fit for the further field application.

Original languageEnglish
Title of host publicationICIEA 2007
Subtitle of host publication2007 Second IEEE Conference on Industrial Electronics and Applications
Pages769-772
Number of pages4
DOIs
StatePublished - 2007
Event2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007 - Harbin, China
Duration: 23 May 200725 May 2007

Publication series

NameICIEA 2007: 2007 Second IEEE Conference on Industrial Electronics and Applications

Conference

Conference2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007
Country/TerritoryChina
CityHarbin
Period23/05/0725/05/07

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