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 |