Enhanced Seasonal Typology-Informed Transit Trip Chaining via Mobile Boarding and Survey Data
Author:
Funder
Federal transit administration
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42421-024-00108-y.pdf
Reference40 articles.
1. Abdalazeem M, Oke J (2023) Extracting spatiotemporal bus passenger trip typologies from noisy mobile ticketing boarding data. Data Sci Transp. https://doi.org/10.1007/s42421-023-00082-x
2. Alsger A, Assemi B, Mesbah M et al (2016) Validating and improving public transport origin–destination estimation algorithm using smart card fare data. Transp Res Part C Emerg Technol 68:490–506. https://doi.org/10.1016/j.trc.2016.05.004
3. Assemi B, Alsger A, Moghaddam M et al (2020) Improving alighting stop inference accuracy in the trip chaining method using neural networks. Public Transp 12(1):89–121. https://doi.org/10.1007/s12469-019-00218-9
4. Bayes T, Price M (1997) LII. An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, F. R. S. communicated by Mr. Price, in a letter to John Canton, A. M. F. R. S. Philos Trans R Soc Lond 53:370–418. https://doi.org/10.1098/rstl.1763.0053
5. Berkson J (1944) Application of the logistic function to bio-assay. J Am Stat Assoc 39(227):357–365. https://doi.org/10.2307/2280041
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