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  4. The Analysis of Mobility Patterns during the COVID-19 Pandemic in Thailand Using Time Series Clustering
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The Analysis of Mobility Patterns during the COVID-19 Pandemic in Thailand Using Time Series Clustering

Author(s)
Supanich, Weeriya
Kulkarineetham, Suwanee
Vanishkorn, Buddhaporn
Date Issued
January 1, 2023
Type
Conference Paper
DOI
10.1109/WCCCT56755.2023.10052489
Abstract
The COVID-19 pandemic has affected the lives, health, economics, and travel of all nations, including Thailand. The purpose of this study is to investigate human mobility patterns during the pandemic. We opted to use the public transportation data from January 1st, 2020 until September 28th, 2022 collected from the Ministry of Transport, Thailand as a data source. We conducted a time series study on trend and seasonality patterns, as well as clustering analysis. It can be concluded that public buses and Bangkok electric trains, nationwide state trains and domestic air travel are the two pairs of public transportation with the most similar usage patterns. Moreover, the majority of personal car travel patterns are quite similar to public buses and Bangkok electric trains during some periods.
Citation
2023 6th World Conference on Computing and Communication Technologies Wccct 2023, 166-170, 2023
Subjects

COVID-19 pandemic

dynamic time warping

human mobility patter...

time series clusterin...

transportation behavi...

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