Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study

Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study

Abstract Accurate classification of rail transit stations is crucial for successful Transit-Oriented Development (TOD) and sustainable urban growth. This paper introduces a novel classification model integrating traditional methodologies with advanced machine learning algorithms. By employing mathem...

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Bibliographic Details
Main Authors: Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Rail Transit Station Classification
Transit Oriented Development
Machine Learning algorithms
Clustering methods
Regression models
Online Access:https://doi.org/10.1038/s41598-024-75541-8
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