Implementation vehicle classification on distributed traffic light control system neural network based

Big Zaman, Wisnu Jatmiko, Adi Wibowo, Elly Matul Imah

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

4 Citations (Scopus)

Abstract

Distributed Traffic System Control System is a real-time adaptive traffic light system with traffic condition for minimize the probabilty of traffic congestion. So far, the research of Distributed Traffic Light Control System has been developed with Principle Component Analysis (PCA) as the recognition method to identify vehicle object. The recognizition can be optimized using classification system that can identify an object to more spesific class as large cars like bus and truck, or minicars like van, jeep, and sedan. Classification systems has be implemented with neural network algorithm specifically Backpropagation, Fuzzy Learning Vector Quantization (FLVQ), and Fuzzy Learning Quantization Particle Swarm Optimization (FLVQ-PSO).

Original languageEnglish
Title of host publicationICACSIS 2011 - 2011 International Conference on Advanced Computer Science and Information Systems, Proceedings
Pages107-112
Number of pages6
Publication statusPublished - 1 Dec 2011
Event2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011 - Jakarta, Indonesia
Duration: 17 Dec 201118 Dec 2011

Publication series

NameICACSIS 2011 - 2011 International Conference on Advanced Computer Science and Information Systems, Proceedings

Conference

Conference2011 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2011
Country/TerritoryIndonesia
CityJakarta
Period17/12/1118/12/11

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