Bike Sharing Demand Forecasting Model
Published: 19 February 2025| Version 1 | DOI: 10.17632/s93xfdrwpx.1
Contributor:
Shin-Hyung ChoDescription
• Exploring the factors affecting the bike-sharing demand on an urban area using multiscale geographically weighted regression (MGWR) • Establishing the bike sharing demand prediction model incorporating the machine learning techniques
Files
Institutions
University of Seoul
Categories
Geospatial Data Repository, Demand Forecasting
Funding
National Research Foundation of Korea
RS-2024-00337626