Investigating the Nonlinear Effect of Built Environment Factors on Metro Station-Level Ridership under Optimal Pedestrian Catchment Areas via the Machine Learning Method

Exploring the built environment factor’s impact on metro ridership can help develop metro station area planning strategies. This is in order to compensate for the shortcomings of previous studies, which mostly used all uniform pedestrian catchment areas (PCA) around metro stations. Beijing was divid...

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Autors principals:	Zhenbao Wang, Shihao Li, Yongjin Li, Dong Liu, Shuyue Liu, Ning Chen
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2023-11-01
Col·lecció:	Applied Sciences
Matèries:	metro station-level ridership built environment eXtreme Gradient Boosting (XGBoost) pedestrian catchment areas (PCA) nonlinear effect
Accés en línia:	https://www.mdpi.com/2076-3417/13/22/12210
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