Comparison of traffic flow prediction based on AR model and BP model
Traffic flow modeling plays an important role in routing，MAC algorithm and protocol designs in vehicular Ad Hoc networks （VANET）. An accurate traffic flow model is crucial to traffic management of an intelligent transportation system （ITS）and information safety in a VANET. Based on Shanghai’s traffi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2016-02-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2016.02.008/ |
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| _version_ | 1841529844258570240 |
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| author | Tingting ZHANG Wuxiong ZHANG Dong PEI Cheng ZHAO Han YU |
| author_facet | Tingting ZHANG Wuxiong ZHANG Dong PEI Cheng ZHAO Han YU |
| author_sort | Tingting ZHANG |
| collection | DOAJ |
| description | Traffic flow modeling plays an important role in routing，MAC algorithm and protocol designs in vehicular Ad Hoc networks （VANET）. An accurate traffic flow model is crucial to traffic management of an intelligent transportation system （ITS）and information safety in a VANET. Based on Shanghai’s traffic flow data，the performance of the two different models was compared using auto regressive（AR）model and back-propagation（BP） network model，and the corresponding prediction result was given. Research finds that both of the two models can efficiently predict the traffic data，but they have different prediction accuracy for the data of different periods. The research result will provide support for future research on ITS and VANET. |
| format | Article |
| id | doaj-art-f4eaa03ab74c425ba1aaacc388c67106 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2016-02-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-f4eaa03ab74c425ba1aaacc388c671062025-01-15T03:15:18ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012016-02-0132555959610120Comparison of traffic flow prediction based on AR model and BP modelTingting ZHANGWuxiong ZHANGDong PEICheng ZHAOHan YUTraffic flow modeling plays an important role in routing，MAC algorithm and protocol designs in vehicular Ad Hoc networks （VANET）. An accurate traffic flow model is crucial to traffic management of an intelligent transportation system （ITS）and information safety in a VANET. Based on Shanghai’s traffic flow data，the performance of the two different models was compared using auto regressive（AR）model and back-propagation（BP） network model，and the corresponding prediction result was given. Research finds that both of the two models can efficiently predict the traffic data，but they have different prediction accuracy for the data of different periods. The research result will provide support for future research on ITS and VANET.http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2016.02.008/VANETITSAR modelBP network modeltraffic flow predicting |
| spellingShingle | Tingting ZHANG Wuxiong ZHANG Dong PEI Cheng ZHAO Han YU Comparison of traffic flow prediction based on AR model and BP model Dianxin kexue VANET ITS AR model BP network model traffic flow predicting |
| title | Comparison of traffic flow prediction based on AR model and BP model |
| title_full | Comparison of traffic flow prediction based on AR model and BP model |
| title_fullStr | Comparison of traffic flow prediction based on AR model and BP model |
| title_full_unstemmed | Comparison of traffic flow prediction based on AR model and BP model |
| title_short | Comparison of traffic flow prediction based on AR model and BP model |
| title_sort | comparison of traffic flow prediction based on ar model and bp model |
| topic | VANET ITS AR model BP network model traffic flow predicting |
| url | http://www.telecomsci.com/zh/article/doi/10.3969/j.issn.1000-0801.2016.02.008/ |
| work_keys_str_mv | AT tingtingzhang comparisonoftrafficflowpredictionbasedonarmodelandbpmodel AT wuxiongzhang comparisonoftrafficflowpredictionbasedonarmodelandbpmodel AT dongpei comparisonoftrafficflowpredictionbasedonarmodelandbpmodel AT chengzhao comparisonoftrafficflowpredictionbasedonarmodelandbpmodel AT hanyu comparisonoftrafficflowpredictionbasedonarmodelandbpmodel |