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A combined forecasting method for traffic volume
2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), 2016In this paper, a combined forecasting method is proposed and applied to traffic volume prediction of 24 hours in advance, called long-term prediction. The combined forecasting model includes two important modules, Kalman filtering module and Markov chains prediction module.
Kaibing Xie, Runmei Li
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Traffic Jam: Handling the Increasing Volume of Mobile Data Traffic
IEEE Vehicular Technology Magazine, 2014Today's mobile operators face significant challenges with handling the ever increasing volume of mobile data traffic. With new mobile communication standards, the mobile backhaul architecture has a clear split of a packet-only data plane and a management plane.
Toktam Mahmoodi, Srini Seetharaman
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Computer, 1970
In the last several years it has become commonplace for representatives of the computer industry and others to speak very convincingly of the enormous amount of data that will soon be transmitted via communication lines throughout the U.S., quoting such authoritative sources as AT&T itself for their information. So forceful have been these remarks that
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In the last several years it has become commonplace for representatives of the computer industry and others to speak very convincingly of the enormous amount of data that will soon be transmitted via communication lines throughout the U.S., quoting such authoritative sources as AT&T itself for their information. So forceful have been these remarks that
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Automatic Generation of Traffic Signal Based on Traffic Volume
2017 IEEE 7th International Advance Computing Conference (IACC), 2017Now day's computer vision techniques are used for analysis of traffic surveillance videos which is gaining more importance. This analysis of videos can be useful for public safety and for traffic management. In recent time, there has been an increased scope for analysis of traffic activity automatically.
T. Sridevi, Kuruva Harinath, P. Swapna
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Study on the Traffic Volume Prediction of Highway Tourist Traffic
2010 International Conference on E-Product E-Service and E-Entertainment, 2010Scientific and accurate forecast of highway tourist traffic volume is the premise of regional tourism transportation development planning. Based on a detailed analysis of the characteristics and influencing factors of highway tourism transportation, Elastic Coefficients Method and Factor Analysis Model were innovatively combined and proposed to ...
Lisha Yu, Xiangyu Yin, Xinlian Xie
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The Distribution of Traffic Volumes
Transportation Science, 1970The distribution of hourly volumes is described and its form and characteristics are discussed. Theoretical models of the distribution are derived so that an estimate of the distribution may be obtained if only a fraction of the traffic data for the year is known.
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Traffic Volume Counting Recorders
Transportation Engineering Journal of ASCE, 1975Traffic volume counting recorders have evolved from the simple cumulative hourly printed recorder to complex telemetry systems. A review of the state-of-the-art of traffic volume counting recorders is presented with emphasis placed on Pennylvania's telecount system and the telemetry systems in Georgia and Michigan. No recommendations are made as to the
Edward L. Priestas, Thomas E. Mulinazzi
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Dispatch management and organization of traffic volumes and traffic
2017The monograph is devoted to the description of adaptation to the real situation and implementation of normative-technical documents regulating the transportation process. First of all, the example of the plan of formation of freight trains shows a rapid response to changes in operational work.
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Traffic Volume Prediction on Busy Road Junctions
Proceedings of the 2018 International Conference on Computing and Big Data, 2018Traffic volume prediction has been a hot spot of the realm of data mining owing to its scientific nature and practical value. The prediction needs an integrated model of linear regression, SARIMA, random forest, KNN, GBDT and the method of weight fusion. This new prediction strategy solves the problem of big forecasting bias produced by a single model.
Yubo Wang +4 more
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