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A User-Centric Machine Learning Framework For Predicting Multi-Modal Accessibility in Transit-Oriented Development Zones For Sustainable Urban Construction in Tier-2 Indian Cities by Shashikant Nishant Sharma is a document available to read on EtoBox.

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This study introduces a user-centric machine learning framework to predict multi-modal accessibility in Transit-Oriented Development zones in tier-2 Indian cities, using survey data from 400 respondents. The research identifies key factors influencing accessibility, with XGBoost performing best among seven evaluated models, and emphasizes the importance of integrating user experiences into urban mobility planning. The framework aims to support equitable and sustainable urban construction, aligning with SDG

Author

Shashikant Nishant Sharma

Language

EN