Investigating the Nonlinear Effect of Land Use and Built Environment on Public Transportation Choice Using a Machine Learning Approach

Investigating the Nonlinear Effect of Land Use and Built Environment on Public Transportation Choice Using a Machine Learning Approach

Understanding the relationship between the demand for public transportation and land use is critical to promoting public-transportation-oriented urban development. Taking Beijing as an example, we took the Public Transportation Index (PTI) during the working day’s early peak hours as the dependent v...

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Bibliographic Details
Main Authors: Zhenbao Wang, Shuyue Liu, Haitao Lian, Xinyi Chen
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Land
Subjects:
land use
built environment
Public Transportation Index
Extreme Gradient Boosting (XGBoost)
Modifiable Areal Unit Problem (MAUP)
explainable machine learning
Online Access:https://www.mdpi.com/2073-445X/13/8/1302

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https://www.mdpi.com/2073-445X/13/8/1302

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