教師資料查詢 | 類別: 會議論文 | 教師: 溫裕弘 Yuh-Horng Wen (瀏覽個人網頁)

標題:Fuzzy data mining and grey recurrent neural network forecasting for traffic information systems
學年94
學期1
發表日期2005/08/15
作品名稱Fuzzy data mining and grey recurrent neural network forecasting for traffic information systems
作品名稱(其他語言)
著者Wen, Yuh-horng; Lee, Tsu-tian; Lee, Tsu-tian
作品所屬單位淡江大學運輸管理學系
出版者IEEE Systems, Man, and Cybernetics Society
會議名稱2005 IEEE International Conference on Information Reuse and Integration
會議地點Las Vegas, Nevada, USA
摘要This study presents a systematic process combining trajfic forecasting and data mining models for traffic information systems. Fuzzy c-means clustering model was developed for mining traffic flow-speed-occupancy relationships, then to extrapolate traffic information. The hybrid grey-based recurrent neural network (G-RNN) was developed for traffic parameter forecasting. G-RNN integrates grey modeling into recurrent neural networks that is capable of dealing with both randomness and spatial-temporal properties in trajfic data implicitly. Field data from Taiwan national freeway was used as an example for testing the proposed models. Study results were shown that the G-RNN model is capable of predicting traffic parameters with a high degree of accuracy. The application presents three clusters built from data and recognized three types of traffic conditions. Study results also showed feasibility of the method for advanced traffic information systems.
關鍵字
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間20050815~20050817
通訊作者
國別中華民國
公開徵稿Y
出版型式紙本
出處2005 IEEE International Conference on Information Reuse and Integration, p.p 356-361
相關連結
Google+ 推薦功能,讓全世界都能看到您的推薦!