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This paper introduces a clustering-regression modeling framework aimed at estimating urban goods transport demand by categorizing establishments into a minimal number of activity categories. The methodology involves a hierarchical clustering analysis followed by a regression-based modeling approach to assess freight trip generation (FTG) using data from the 2011-2012 Freight Trip Survey in the Paris Region. The resulting models demonstrate robustness and applicability to various French cities, providing a s

Author

Boran zkut

Language

EN