Work

DMP: Predicting Bike Rental Demand for Smarter Urban Mobility

Year: 2025

Type: article

Abstract: This project focuses on predicting bike rental demand in Seoul using machine learning techniques. It includes an XGBoost-based model trained on publicly available Seoul bike rental data. The repository contains the trained model, the code for training and evaluation, prediction results in CSV format, and a visualization comparing the ground truth and predicted values

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15298276

Author: Kobler, Lukas

Institution: TU Wien

Language: English

Topic: Urban Transport and Accessibility

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6930616368

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