教師資料查詢 | 類別: 會議論文 | 教師: 李英豪 LEE YING-HAUR (瀏覽個人網頁)

標題:Applications of Artificial Neural Networks to Pavement Prediction Modeling: A Case Study
學年102
學期2
發表日期2014/05/25
作品名稱Applications of Artificial Neural Networks to Pavement Prediction Modeling: A Case Study
作品名稱(其他語言)
著者Lee, Ying-Haur; Ker, Hsiang-Wei; Liu, Yao-Bin
作品所屬單位淡江大學土木工程學系
出版者VirginiaAmerican Society of Civil Engineers
會議名稱The 10th Asia
Pacific Transportation Development Conference and 27th ICTPA Annual
Conference: Challenges and Recent Advances in Sustainable Transportation
System – Planning, Design, Build, Management and Maintenance
會議地點Beijing, China
摘要Artificial neural networks (ANN) have been used in many pavement prediction modeling analyses. However, the convergence characteristics and model selection guidelines are rarely studied duc to the requirement of extensive network training time. Thus, the techniques and applications of back propagation neural networks were briefly reviewed. Three ANN models were developed using deflection databases generated by factorial BISAR runs. A study of the convergence characteristics indicated that the resulting ANN model using all dominating dimensionless parameters was proved to have higher accuracy and require less network training time and data than the other counterpart using purely input parameters. Increasing the complexity of ANN models does not necessarily improve the modeling statistics. With the incorporation of subject-related engineering and statistical knowledge into the modeling process, reasonably good predictions may be achieved with more convincing generalization and explanation yet requiring minimal amount oftime and effort.
關鍵字Pavement deflection, prediction modeling, artificial neural networks, dimensional analysis, convergence
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20140525~20140527
通訊作者Lee, Y. H.
國別中國
公開徵稿Y
出版型式紙本
出處PROCEEDINGS OF THE 10TH ASIA PACIFIC TRANSPORTATION DEVELOPMENT CONFERENCE, pp.289-295
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