A computerized feature reduction using cluster methods for accident duration forecasting on freeway

Ying Lee, Chien-Hung Wei

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

This study creates two Artificial Neural Network-based models and provides a sequential forecast of accident duration from the accident notification to the accident site clearance. With these two models, the estimated duration time can be provided by plugging in relevant traffic data as soon as an accident is notified. To reduce data feature, cluster method can decreases the number of model inputs and preserves the relevant traffic characteristics with fewer inputs. This study shows proposed models are feasible ones in the Intelligent Transportation Systems (ITS) context.

原文English
主出版物標題Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008
發行者IEEE Computer Society
頁面1459-1464
頁數6
ISBN(列印)9780769534732
DOIs
出版狀態Published - 2008 1月 1
事件3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008 - Yilan, Taiwan
持續時間: 2008 12月 92008 12月 12

出版系列

名字Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008

Other

Other3rd IEEE Asia-Pacific Services Computing Conference, APSCC 2008
國家/地區Taiwan
城市Yilan
期間08-12-0908-12-12

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 軟體
  • 電氣與電子工程

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