Generating and understanding human daily activity sequences using Time-Varying Markov Chain models

Author:

Wang WeiyingORCID,Osaragi ToshihiroORCID

Funder

Japan Science and Technology Agency

Publisher

Elsevier BV

Subject

Transportation,Geography, Planning and Development

Reference51 articles.

1. Microscopic activity sequence generation: A multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes;Ahmed;Transportation,2021

2. Daily activity pattern recognition by using support vector machines with multiple classes;Allahviranloo;Transportation Research Part b: Methodological,2013

3. Modeling the activity profiles of a population;Allahviranloo;Transportmetrica b: Transport Dynamics,2016

4. A learning-based transportation oriented simulation system;Arentze;Transportation Research Part b: Methodological,2004

5. Framework for the development of the agent-based dynamic activity planning and travel scheduling (ADAPTS) model;Auld;Transportation Letters,2009

Cited by 2 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. TriFusion hybrid model for human activity recognition;Signal, Image and Video Processing;2024-08-12

2. Learning Daily Human Mobility with a Transformer-Based Model;ISPRS International Journal of Geo-Information;2024-01-24

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