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dc.contributor.authorTong Mingrong
dc.contributor.authorXue Hengxin
dc.date.accessioned2017-05-08T22:05:03Z
dc.date.available2017-05-08T22:05:03Z
dc.date.copyrightDecember 2008
dc.date.issued2008
dc.identifier.otherjhtrcq%2E0000255.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl/handle/yetl/70816
dc.description.abstractIn order to improve the accuracy of seasonal highway traffic volume forecasting, a general expression of seasonal ARIMA model with periodicity was presented based on the normal ARIMA model, and then the procedures of modeling and forecasting via seasonal ARIMA model were provided. In the feasibility-study experiment, the seasonal length was calculated by Fourier period analysis method, the test of the stationarity of the time series, and identifying, establishing, choosing and forecasting of the model were done by Eviews software. Compared with three normal seasonal forecasting models (grouped regression model, variable seasonal index forecasting model and seasonal regression model), the seasonal ARIMA model can obtain the highest accuracy in forecasting. The research result is significant to forecast highway traffic volume more accurately.
dc.publisherAmerican Society of Civil Engineers
dc.titleHighway Traffic Volume Forecasting Based on Seasonal ARIMA Model
dc.typeJournal Paper
dc.journal.volume3
dc.journal.issue2
dc.journal.titleJournal of Highway and Transportation Research and Development (English Edition)
dc.identifier.doi10.1061/JHTRCQ.0000255
dc.treeJournal of Highway and Transportation Research and Development (English Edition):;2008:;Volume ( 003 ):;issue: 002
dc.contenttypeFulltext


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