Decoding Urban Mobility: Application of Natural Language Processing and Machine Learning to Activity Pattern Recognition, Prediction, and Temporal Transferability Examination-Reference-Cited by-同舟云学术

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Decoding Urban Mobility: Application of Natural Language Processing and Machine Learning to Activity Pattern Recognition, Prediction, and Temporal Transferability Examination

Published:2024-07 Issue:7 Volume:25 Page:7151-7173
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Chen Mingyang¹^ORCID,Yuan Quan¹,Yang Chao¹^ORCID,Zhang Yuliang²

Affiliation:

1. Urban Mobility Institute, Tongji University, Shanghai, China

2. Intelligent Transportation System Research Center, Hangzhou City University, Hangzhou, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10379536.pdf?arnumber=10379536

Reference31 articles.

1. Activity-based models of travel demand: promises, progress and prospects

2. SMASH (Simulation Model of Activity Scheduling Heuristics): Some Simulations

3. Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns

4. Activity-Travel Scheduling and Rescheduling Decision Processes: Empirical Estimation of Aurora Model

5. Florida Activity Mobility Simulator

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Large Language Models for Intelligent Transportation: A Review of the State of the Art and Challenges;Applied Sciences;2024-08-23

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