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dc.contributor.authorJou, YJen_US
dc.contributor.authorLee, TTen_US
dc.contributor.authorLan, CLen_US
dc.contributor.authorHsu, CHen_US
dc.date.accessioned2014-12-08T15:26:18Z-
dc.date.available2014-12-08T15:26:18Z-
dc.date.issued2003en_US
dc.identifier.isbn0-7803-8125-4en_US
dc.identifier.urihttp://hdl.handle.net/11536/18678-
dc.description.abstractThe purpose of this study is to develop a freeway travel time prediction. model and, combined with real-time database, to obtain the most recise travel time prediction. First, a Grey System Theory for travel time prediction is developed, and then Markov Bias Correction mechanism is used for bias correction. Prediction is divided into "data-of-week" in time category because of that, travel time is corresponding to travel pattern and,travel pattern itself is highly related to whether it is weekday or weekend. In the link section, this study divided the path into pairs of interchanges because of the information obtained. And then, construct a real-time database, and connect to Taiwan Area National Freeway Bureau via internet for real-time travel speed.-and uses this information on freeway travel time prediction. Besides prediction, this study also. uses this information for calibration.en_US
dc.language.isoen_USen_US
dc.subjectgrey systemen_US
dc.subjectreal-time travel time predictionen_US
dc.titleThe implementation of Markov bias corrected grey system in freeway travel time predictionen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2en_US
dc.citation.spage832en_US
dc.citation.epage835en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000188415300153-
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