Macroscopic traffic flow model calibration using different optimization algorithms
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DOI: 10.1007/s12351-015-0219-4
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Cited by:
- Yan, Fei & Qiu, Jiangchen & Tian, Jianyan, 2022. "An iterative learning identification strategy for nonlinear macroscopic traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
- Čičić, Mladen & Johansson, Karl Henrik, 2022. "Front-tracking transition system model for traffic state reconstruction, model learning, and control with application to stop-and-go wave dissipation," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 212-236.
- Mohammadian, Saeed & Zheng, Zuduo & Haque, Md. Mazharul & Bhaskar, Ashish, 2021. "Performance of continuum models for realworld traffic flows: Comprehensive benchmarking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 132-167.
- Farzaneh Ferdowsi & Hamid Reza Maleki & Sanaz Rivaz, 2020. "Air refueling tanker allocation based on a multi-objective zero-one integer programming model," Operational Research, Springer, vol. 20(4), pages 1913-1938, December.
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Keywords
Macroscopic traffic flow models; Model calibration; Comparison of optimization algorithms;All these keywords.
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