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A validation measure for computational scheduler activity-based transportation models based on sequence alignment methods

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  • George Sammour
  • Koen Vanhoof

Abstract

In recent decades, activity-based transportation models have gained growing attention, due to their strong foundation in behavioral theory and ability to model the response of individuals to travel demand management policies. Hence, researchers have become increasingly interested in analyzing and predicting individuals’ decisions about activity participation. This paper investigates the reliability and uncertainty of computational process activity-based models. The design of the scheduling process model is experimented with by introducing an alternative decision sequence. The results provide additional information to better understand the process model’s reliability and behavior. Furthermore, the findings show that the current sequence of decision steps in the process model in ALBATROSS achieves satisfactory work activity schedules. Finally, the study concludes that using a decision tree model achieves a better performance than using diverse data mining approaches.

Suggested Citation

  • George Sammour & Koen Vanhoof, 2018. "A validation measure for computational scheduler activity-based transportation models based on sequence alignment methods," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(7), pages 736-751, October.
  • Handle: RePEc:taf:transp:v:41:y:2018:i:7:p:736-751
    DOI: 10.1080/03081060.2018.1504183
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    Cited by:

    1. Allahviranloo, Mahdieh & Aissaoui, Leila, 2019. "A comparison of time-use behavior in metropolitan areas using pattern recognition techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 271-287.

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