書誌事項
- タイトル別名
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- Online-learning Type of Traveling Time Prediction Model in Expressway
- ジドウ ガクシュウ キノウ オ ソナエタ コウソク ドウロ リョコウ ジカン
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抄録
In expressway, there exist a lot of requirements for traveling time prediction as the information on express way traffic-flow. It is a problem to be solved to predict traveling time with high accuracy in case traffic-flow changes dynamically like the beginning or the end of traffic congestion. It is therefore important to make the trafficsimulation model using time-series data by vehicle detectors. In this case, it is necessary to cope with secular change of traffic-flow characteristics like constructions of new expressways or environment condition changes. Thispaper proposes the new traffic-flow prediction system which has the model learning function by time-series data processing. The system makes the relation model between traffic density and vehicle velocity using neural networks. The neural networks is used as on-line learning model VENN(Vehicle velocity Estimation model on Neural Network). The system simulates the traffic-flow using the VENN and predicts traveling time using the simulation results. The proposed system was already estimated in the actual expressway, which ended in satisfactory results.
収録刊行物
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- 電気学会論文誌D(産業応用部門誌)
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電気学会論文誌D(産業応用部門誌) 117 (8), 980-985, 1997
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390282679635472256
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- NII論文ID
- 10002724992
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- NII書誌ID
- AN10012320
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- ISSN
- 13488163
- 09136339
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- NDL書誌ID
- 4267307
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- データソース種別
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- JaLC
- NDL
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可