Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network

Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network

This study examines travel mode choice behavior within the context of Thailand’s emerging high-speed rail (HSR) development. It conducts a comparative assessment of predictive capabilities between the conventional Multinomial Logit (MNL) framework and advanced data-driven methodologies, including gr...

Full description

Saved in:
Bibliographic Details
Main Authors: Chinnakrit Banyong, Natthaporn Hantanong, Supanida Nanthawong, Chamroeun Se, Panuwat Wisutwattanasak, Thanapong Champahom, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Big Data and Cognitive Computing
Subjects:
behavioral machine intelligence
neural decision systems
Shapley Additive Explanations
comparative analysis
Online Access:https://www.mdpi.com/2504-2289/9/6/155
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2504-2289/9/6/155

Similar Items