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A comparative study of a hybrid logit-Fratar and neural network models for trip distribution: Case of the city of Isfahan

Shir Mohammadli, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1002/atr.143
  3. Abstract:
  4. This paper introduces a new procedure to forecast the future O/D demand. It is a hybrid of logit and Fratar model. The hybrid model has the long run, policy sensitive, characteristic of a logit model, calibrated at sector-level with little/no zero O/D cells. This feature, joint with a Fratar-type operation at zonal level within a sector, gives a better performance to this model than either of the two types of the models alone. The performance of the hybrid model is contrasted with a neural network model, and shows encouraging results in a real case
  5. Keywords:
  6. Hybrid Logit-Fratar ; Neural network ; Comparative studies ; Fratar model ; Hybrid Logit-Fratar ; Hybrid model ; Logit models ; Neural network model ; Trip distribution ; Mathematical models ; Neural networks
  7. Source: Journal of Advanced Transportation ; Volume 45, Issue 1 , 2011 , Pages 80-93 ; 01976729 (ISSN)
  8. URL: http://onlinelibrary.wiley.com/doi/10.1002/atr.143/abstract