A genetic algorithm-based method for improving quality of travel time prediction intervals Khosravi, Abbas, Mazloumi, Ehsan, Nahavandi, Saeid, Creighton, Doug and Van Lint, J. W. C. 2011, A genetic algorithm-based method for improving quality of travel time prediction intervals, Transportation research part C, vol. 19, no. 6, pp. 1364-1376, doi: 10.1016/j.trc.2011.04.002. Attached Files Name Description MIMEType Size Downloads Title A genetic algorithm-based method for improving quality of travel time prediction intervals Author(s) Khosravi, Abbas orcid.org/0000-0001-6927-0744 Mazloumi, Ehsan Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Creighton, Doug orcid.org/0000-0002-9217-1231 Van Lint, J. W. C. Journal name Transportation research part C Volume number 19 Issue number 6 Start page 1364 End page 1376 Total pages 13 Publisher Pergamon Place of publication Oxford, United Kingdom Publication date 2011-12 ISSN 0968-090X 1879-2359 Keyword(s) genetic algorithm neural network prediction interval travel time Language eng DOI 10.1016/j.trc.2011.04.002 Field of Research 109999 Technology not elsewhere classified Socio Economic Objective 970110 Expanding Knowledge in Technology HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2011, Elsevier Ltd. Persistent URL http://hdl.handle.net/10536/DRO/DU:30040636 Document type: Journal Article Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 05 Dec 2011, 12:52:35 EST Thu, 05 Jan 2012, 15:05:52 EST Thu, 05 Jan 2012, 15:08:01 EST Thu, 31 May 2012, 15:29:55 EST Thu, 31 May 2012, 15:45:07 EST Fri, 01 Jun 2012, 10:00:08 EST Mon, 17 Jun 2013, 17:21:59 EST Wed, 02 Jul 2014, 15:29:10 EST Fri, 17 Oct 2014, 11:11:07 EST Filtered Full Citation counts:   Cited 59 times in TR Web of Science Cited 67 times in Scopus Search Google Scholar Access Statistics: 705 Abstract Views, 5 File Downloads  -  Detailed Statistics Created: Mon, 05 Dec 2011, 12:52:35 EST

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