The usefulness of the Sequence Alignment Methods in validating rule-based activity-based forecasting models
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DOI: 10.1007/s11116-012-9406-9
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Cited by:
- Allahviranloo, Mahdieh & Recker, Will, 2013. "Daily activity pattern recognition by using support vector machines with multiple classes," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 16-43.
- Meead Saberi & Taha H. Rashidi & Milad Ghasri & Kenneth Ewe, 2018. "A Complex Network Methodology for Travel Demand Model Evaluation and Validation," Networks and Spatial Economics, Springer, vol. 18(4), pages 1051-1073, December.
- Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 2021. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 48(3), pages 1481-1502, June.
- Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 0. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 0, pages 1-22.
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Keywords
Activity-based models validation; Sequence Alignment Methods; Classification methods; Process models;All these keywords.
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