Bike Sharing Demand Forecasting Model

Published: 19 February 2025| Version 1 | DOI: 10.17632/s93xfdrwpx.1
Contributor:
Shin-Hyung Cho

Description

• 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

Licence