Showing 161 - 180 results of 210 for search 'The Shenzhen Experiment', query time: 0.06s Refine Results
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    Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion by Chenxi LIU, Dong WANG, Huiling CHEN, Renfa LI

    Published 2021-03-01
    “…By effectively capturing the spatio-temporal characteristics of urban private car travel, a multi-source heterogeneous data fusion model for private car volume prediction was proposed.Firstly, private car trajectory and area-of-interest data were integrated.Secondly, the spatio-temporal correlations between private car travel and urban areas were modeled through multi-view spatio-temporal graphs, the multi-graph convolution-attention network (MGC-AN) was proposed to extract the spatio-temporal characteristics of private car travel.Finally, the spatio-temporal characteristics and external characteristics such as weather were integrated for joint prediction.Experiments were conducted on real datasets, which were collected in Changsha and Shenzhen.The experimental results show that, compared with the existing prediction model, the root mean square error of the MGC-AN is reduced 11.3%~20.3%, and the average absolute percentage error is reduced 10.8%~36.1%.…”
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    Real-time predication and navigation on traffic congestion model with equilibrium Markov chain by Yan Zheng, Yanran Li, Chung-Ming Own, Zhaopeng Meng, Mengya Gao

    Published 2018-04-01
    “…Accordingly, by dividing the real-time Global Positioning System data of taxis in Shenzhen city into 50 regions, the equilibrium Markov chain model was designed for dispatching vehicles and applied to ease the city congestion. …”
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