The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/51fa919d-bc31-4e55-92ac-6fc67ff50fcc

Eftekhar, Zahra; Behrouzi, Saman; Panchamy Krishnakumari; Pel, Adam; van Lint, Hans (2024): The codes associated with the publication: The Role of Spatial Features and Adjacency in Data-driven Short-term Prediction of Trip Production: An Exploratory Study in the Netherlands. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/51fa919d-bc31-4e55-92ac-6fc67ff50fcc.v1

Software

• Civil Engineering
• Urban and Regional Planning
• Environmentally Sustainable Transport
• Ground Transport
• Other Transport
• Engineering
• Transport
• Built Environment and Design

demand prediction, graph convolution, residual analysis, spatial scale, spatial-temporal pattern, trip production

MIT

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Zahra Eftekhar , Saman Behrouzi , Panchamy Krishnakumari , Adam Pel , Hans van Lint

This repository contains the codes associated with the research paper titled "The Role of Spatial Features and Adjacency in Data-driven Short-term Prediction of Trip Production: An Exploratory Study in the Netherlands". The paper is currently under review for publication in the IEEE Transactions on Intelligent Transportation Systems. This code repo is intended to perform analysis on the temporal patterns prediction of travel demand in the Netherlands. The data source needed for running this code can be found under the name " The input data associated with the publication: The Role of Spatial Features and Adjacency in Data-driven Short-term Prediction of Trip Production: An Exploratory Study in the Netherlands".

• 2024-09-30 first online, published, posted

4TU.ResearchData

scripts/ .py and .ipynb; package management/ requirements.txt; README file/ .md

https://doi.org/10.4121/835e7093-024c-4bed-b7e5-28f1582f5998

• MiRRORS (grant code 16270) NWO/TTW

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning