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Using machine learning to examine freight network spatial v..:
Paul M. Johnson
;
William Barbour
;
Janey V. Camp
.
http://www.sciencedirect.com/science/article/pii/S2590198222000793. , 2022
Link:
https://doi.org/10.1016/j.trip.2022.100617
RT Journal T1
Using machine learning to examine freight network spatial vulnerabilities to disasters: A new take on partial dependence plots
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:fc4bb1b4da9646cfa6d1eaef4a3d7993&Exemplar=1&LAN=DE A1 Paul M. Johnson A1 William Barbour A1 Janey V. Camp A1 Hiba Baroud PB Elsevier YR 2022 K1 Network vulnerability K1 Transportation disruption analysis K1 Partial dependence plot K1 Gradient boosting machine K1 Freight simulation K1 Transportation and communications K1 HE1-9990 JF http://www.sciencedirect.com/science/article/pii/S2590198222000793 LK http://dx.doi.org/https://doi.org/10.1016/j.trip.2022.100617 DO https://doi.org/10.1016/j.trip.2022.100617 SF ELIB - SuUB Bremen
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