Adaptive hybrid fuzzy rule-based system approach for modeling and predicting urban traffic flow

Dimitriou, L; Tsekeris, T; Stathopoulos, A

dc.contributor.author	Dimitriou, L	en
dc.contributor.author	Tsekeris, T	en
dc.contributor.author	Stathopoulos, A	en
dc.date.accessioned	2014-03-01T01:27:49Z
dc.date.available	2014-03-01T01:27:49Z
dc.date.issued	2008	en
dc.identifier.issn	0968-090X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18595
dc.subject	Fuzzy rule-based systems	en
dc.subject	Global optimization	en
dc.subject	Short-term forecasting	en
dc.subject	Traffic flow modeling	en
dc.subject	Urban networks	en
dc.subject.classification	Transportation Science & Technology	en
dc.subject.other	Algorithms	en
dc.subject.other	Computer networks	en
dc.subject.other	Data structures	en
dc.subject.other	File organization	en
dc.subject.other	Forecasting	en
dc.subject.other	Function evaluation	en
dc.subject.other	Fuzzy logic	en
dc.subject.other	Fuzzy rules	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Knowledge based systems	en
dc.subject.other	Mathematical models	en
dc.subject.other	Metropolitan area networks	en
dc.subject.other	Model structures	en
dc.subject.other	Network protocols	en
dc.subject.other	Statistical methods	en
dc.subject.other	Statistics	en
dc.subject.other	Traffic surveys	en
dc.subject.other	Variational techniques	en
dc.subject.other	(min ,max ,+) functions	en
dc.subject.other	Elsevier (CO)	en
dc.subject.other	hybrid fuzzy	en
dc.subject.other	Multivariate data	en
dc.subject.other	Off-line applications	en
dc.subject.other	On line applications	en
dc.subject.other	On line tuning	en
dc.subject.other	Short-term forecasting	en
dc.subject.other	Statistical techniques	en
dc.subject.other	Traffic conditions	en
dc.subject.other	Traffic data	en
dc.subject.other	traffic flowing	en
dc.subject.other	Univariate	en
dc.subject.other	Urban arterial networks	en
dc.subject.other	Urban traffic	en
dc.subject.other	Membership functions	en
dc.subject.other	adaptive management	en
dc.subject.other	forecasting method	en
dc.subject.other	fuzzy mathematics	en
dc.subject.other	genetic algorithm	en
dc.subject.other	modeling	en
dc.subject.other	multivariate analysis	en
dc.subject.other	optimization	en
dc.subject.other	traffic management	en
dc.subject.other	transportation planning	en
dc.subject.other	urban transport	en
dc.title	Adaptive hybrid fuzzy rule-based system approach for modeling and predicting urban traffic flow	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.trc.2007.11.003	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.trc.2007.11.003	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	This paper presents an adaptive hybrid fuzzy rule-based system (FRBS) approach for the modeling and short-term forecasting of traffic flow in urban arterial networks. Such an approach possesses the advantage of suitably addressing data imprecision and uncertainty, and it enables the incorporation of,expert's knowledge on local traffic conditions within the model structure. The model employs univariate and multivariate data structures and uses a Genetic Algorithm for the offline and online tuning of the FRBS membership functions according to the prevailing traffic conditions. The results obtained from the online application of the proposed FRBS are found to overperform those of the offline application and conventional statistical techniques, when modeling both univariate and multivariate traffic data corresponding to a real signalized urban arterial corridor. (c) 2007 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Transportation Research Part C: Emerging Technologies	en
dc.identifier.doi	10.1016/j.trc.2007.11.003	en
dc.identifier.isi	ISI:000258344800003	en
dc.identifier.volume	16	en
dc.identifier.issue	5	en
dc.identifier.spage	554	en
dc.identifier.epage	573	en