Art

J-GLOBAL ID：202102221869408985   Reference number：21A0036993

Prediction of Highway Tunnel Pavement Performance Based on Digital Twin and Multiple Time Series Stacking

ディジタルツインと多重時系列積層に基づく道路トンネル舗装性能の予測【JST・京大機械翻訳】

Author (7)： Yu Gang (SILC Business School, Shanghai University, Shanghai 201800, China) ,  Yu Gang (SHU-SUCG Research Centre for Building Industrialization, Shanghai University, Shanghai 200072, China) ,  Zhang Shuang (SILC Business School, Shanghai University, Shanghai 201800, China) ,  Zhang Shuang (SHU-SUCG Research Centre for Building Industrialization, Shanghai University, Shanghai 200072, China) ,  Hu Min (SILC Business School, Shanghai University, Shanghai 201800, China) ,  Hu Min (SHU-SUCG Research Centre for Building Industrialization, Shanghai University, Shanghai 200072, China) ,  Wang Y. Ken (Computer Information Systems and Technology, University of Pittsburgh, Pittsburgh 15260, PA, USA)
Material： Advances in Civil Engineering (Web)
Volume： 2020  Page： Null  Publication year： 2020 
JST Material Number： U7655A  ISSN： 1687-8086  Document type： Article
Article type： 原著論文  Country of issue： United Kingdom (GBR)  Language： ENGLISH (EN)

Abstract/Point： The existing pavement performa...

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Thesaurus term： prediction technique ,  optimization ,  expressway ,  *road ,  neural network(biomodel) ,  feature extraction ,  *road tunnel ,  *multiplex ,  machine learning ,  prediction model
Semi thesaurus term： 学習者 ,  ブースティング ,  ランダムフォレスト ,  サポートベクトル回帰 ,  ハイパーパラメータ , 【Automatic Indexing@JST】

JST classification (1)： Pavement in general  (RC04010K)

Reference (57)：

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Terms in the title (6)： ディジタル ,  多重 ,  時系列 ,  道路トンネル ,  舗装性能 ,  予測