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On the imputation of missing data for road traffic forecasting: New insights and novel techniques

  • Published:2018-05 Issue: Volume:90 Page:18-33
  • ISSN:0968-090X
  • Container-title:Transportation Research Part C: Emerging Technologies
  • language:en
  • Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Laña Ibai,Olabarrieta Ignacio (Iñaki),Vélez Manuel,Del Ser Javier

Funder

Basque Government

European Commission

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference55 articles.

1. Traffic flow prediction for road transportation networks with limited traffic data;Abadi;IEEE Trans. Intell. Transport. Syst.,2015

2. Using stated preference data for studying the effect of advanced traffic information on drivers’ route choice;Abdel-Aty;Transport. Res. Part C: Emerg. Technol.,1997

3. Dealing with missing data in MSPC: several methods, different interpretations, some examples;Arteaga;J. Chemometr.,2002

4. Matrix and tensor based methods for missing data estimation in large traffic networks;Asif;IEEE Trans. Intell. Transport. Syst.,2016

5. Online method to impute missing loop detector data for urban freeway traffic control;Bie;Transport. Res. Rec.: J. Transport. Res. Board,2016

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