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Prediction of Duration of Traffic Incidents by Hybrid Deep Learning Based on Multi-Source Incomplete Data.
Shang, Qiang; Xie, Tian; Yu, Yang.
Affiliation
  • Shang Q; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China.
  • Xie T; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China.
  • Yu Y; School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China.
Int J Environ Res Public Health ; 19(17)2022 09 01.
Article in En | MEDLINE | ID: mdl-36078617
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Int J Environ Res Public Health Year: 2022 Document type: Article Affiliation country: China Country of publication: Switzerland
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Int J Environ Res Public Health Year: 2022 Document type: Article Affiliation country: China Country of publication: Switzerland