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An object-oriented neural network approach to short-term traffic forecasting

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  • Dia, Hussein

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  • Dia, Hussein, 2001. "An object-oriented neural network approach to short-term traffic forecasting," European Journal of Operational Research, Elsevier, vol. 131(2), pages 253-261, June.
  • Handle: RePEc:eee:ejores:v:131:y:2001:i:2:p:253-261
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    References listed on IDEAS

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    1. Okutani, Iwao & Stephanedes, Yorgos J., 1984. "Dynamic prediction of traffic volume through Kalman filtering theory," Transportation Research Part B: Methodological, Elsevier, vol. 18(1), pages 1-11, February.
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    Cited by:

    1. Yikang Rui & Yannan Gong & Yan Zhao & Kaijie Luo & Wenqi Lu, 2023. "Predicting Traffic Flow Parameters for Sustainable Highway Management: An Attention-Based EMD–BiLSTM Approach," Sustainability, MDPI, vol. 16(1), pages 1-17, December.
    2. Alireza Ermagun & David Levinson, 2017. "Spatiotemporal Short-term Traffic Forecasting using the Network Weight Matrix and Systematic Detrending," Working Papers 000166, University of Minnesota: Nexus Research Group.
    3. Zhao, Jiangjiang & Ma, Tieju, 2016. "Optimizing layouts of initial AFV refueling stations targeting different drivers, and experiments with agent-based simulations," European Journal of Operational Research, Elsevier, vol. 249(2), pages 706-716.
    4. Sohani Liyanage & Hussein Dia, 2020. "An Agent-Based Simulation Approach for Evaluating the Performance of On-Demand Bus Services," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
    5. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    6. Hongxia Ge & Siteng Li & Rongjun Cheng & Zhenlei Chen, 2022. "Self-Attention ConvLSTM for Spatiotemporal Forecasting of Short-Term Online Car-Hailing Demand," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    7. Lu, Xijin & Ma, Changxi & Qiao, Yihuan, 2021. "Short-term demand forecasting for online car-hailing using ConvLSTM networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    8. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Nataša Glišović & Miloš Milenković & Nebojša Bojović & Libor Švadlenka & Zoran Avramović, 2016. "A hybrid model for forecasting the volume of passenger flows on Serbian railways," Operational Research, Springer, vol. 16(2), pages 271-285, July.
    10. Yang Yue & Anthony Gar-On Yeh, 2008. "Spatiotemporal Traffic-Flow Dependency and Short-Term Traffic Forecasting," Environment and Planning B, , vol. 35(5), pages 762-771, October.
    11. Chrobok, R. & Kaumann, O. & Wahle, J. & Schreckenberg, M., 2004. "Different methods of traffic forecast based on real data," European Journal of Operational Research, Elsevier, vol. 155(3), pages 558-568, June.
    12. Shahaboddin Shamshirband & Lejla Banjanovic-Mehmedovic & Ivan Bosankic & Suad Kasapovic & Ainuddin Wahid Bin Abdul Wahab, 2016. "Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-12, May.
    13. Chen, Yi-Ting & Sun, Edward W. & Chang, Ming-Feng & Lin, Yi-Bing, 2021. "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0," International Journal of Production Economics, Elsevier, vol. 238(C).
    14. Matheus S Quessada & Rickson S Pereira & William Revejes & Bruno Sartori & Euclydes N Gottsfritz & Douglas D Lieira & Marco AC da Silva & Geraldo P Rocha Filho & Rodolfo I Meneguette, 2020. "ITSMEI: An intelligent transport system for monitoring traffic and event information," International Journal of Distributed Sensor Networks, , vol. 16(10), pages 15501477209, October.

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