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 Virginia：American 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 en
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 CHN
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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