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您的检索式：作者名="Vincent C.S.LEE"
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| 1 | Research and applications of artificial neural network in pavement engineering:A state-of-the-art review显示文摘Given the great advancements in soft computing and data science,artificial neural network(ANN)has been explored and applied to handle complicated problems in the field of pavement engineering.This study conducted a state-of-the-art review for surveying the recent progress of ANN application at different stages of pavement engineering,including pavement design,construction,inspection and monitoring,and maintenance.This study focused on the papers published over the last three decades,especially the studies conducted since 2013.Through literature retrieval,a total of 683 papers in this field were identified,among which 143 papers were selected for an in-depth review.The ANN architectures used in these studies mainly included multi-layer perceptron neural network(MLPNN),convolutional neural network(CNN)and recurrent neural network(RNN)for processing one-dimensional data,two-dimensional data and time-series data.CNN-based pavement health inspection and monitoring attracted the largest research interest due to its potential to replace human labor.While ANN has been proved to be an effective tool for pavement material design,cost analysis,defect detection and maintenance planning,it is facing huge challenges in terms of data collection,parameter optimization,model transferability and low-cost data annotation.More attention should be paid to bring multidisciplinary techniques into pavement engineering to tackle existing challenges and widen future opportunities. | Xu Yang Jinchao Guan Ling Ding Zhanping You Vincent C.S.Lee Mohd Rosli Mohd Hasan Xiaoyun Cheng | 2021 | Journal of Traffic and Transportation Engineering(English Edition)2021，8，6： | 2 |
| 2 | Conceptualizing Mining of Firm's Web Log Files显示文摘In this era of a data-driven society, useful data(Big Data) is often unintentionally ignored due to lack of convenient tools and expensive software. For example, web log files can be used to identify explicit information of browsing patterns when users access web sites. Some hidden information,however, cannot be directly derived from the log files. We may need external resources to discover more knowledge from browsing patterns. The purpose of this study is to investigate the application of web usage mining based on web log files. The outcome of this study sets further directions of this investigation on what and how implicit information embedded in log files can be efficiently and effectively extracted. Further work involves combining the use of social media data to improve business decision quality. | Ruangsak TRAKUNPHUTTHIRAK Yen CHEUNG Vincent C.S.LEE | 2017 | Journal of Systems Science and Information2017，8，6： | 0 |
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