Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion
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...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2021-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021018/ |
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| _version_ | 1850123224683118592 |
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| author | Chenxi LIU Dong WANG Huiling CHEN Renfa LI |
| author_facet | Chenxi LIU Dong WANG Huiling CHEN Renfa LI |
| author_sort | Chenxi LIU |
| collection | DOAJ |
| description | 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%. |
| format | Article |
| id | doaj-art-ddba92e16597440ba7e54ffc60bb390b |
| institution | OA Journals |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-ddba92e16597440ba7e54ffc60bb390b2025-08-20T02:34:39ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-03-0142546459740767Study of forecasting urban private car volumes based on multi-source heterogeneous data fusionChenxi LIUDong WANGHuiling CHENRenfa LIBy 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%.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021018/multi-source heterogeneous dataarea of interestgraph neural network |
| spellingShingle | Chenxi LIU Dong WANG Huiling CHEN Renfa LI Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion Tongxin xuebao multi-source heterogeneous data area of interest graph neural network |
| title | Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion |
| title_full | Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion |
| title_fullStr | Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion |
| title_full_unstemmed | Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion |
| title_short | Study of forecasting urban private car volumes based on multi-source heterogeneous data fusion |
| title_sort | study of forecasting urban private car volumes based on multi source heterogeneous data fusion |
| topic | multi-source heterogeneous data area of interest graph neural network |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021018/ |
| work_keys_str_mv | AT chenxiliu studyofforecastingurbanprivatecarvolumesbasedonmultisourceheterogeneousdatafusion AT dongwang studyofforecastingurbanprivatecarvolumesbasedonmultisourceheterogeneousdatafusion AT huilingchen studyofforecastingurbanprivatecarvolumesbasedonmultisourceheterogeneousdatafusion AT renfali studyofforecastingurbanprivatecarvolumesbasedonmultisourceheterogeneousdatafusion |