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Authors: Zong-Kai Lai 1 ; Yi-Ting Chiang 1 ; Tsan-sheng Hsu 2 and Hung-Jui Chang 1

Affiliations: 1 Department of Applied Mathematics, Chung Yuan Christian University, Taoyuan, Taiwan, Republic of China ; 2 Institute of Information Science, Academia Sinica, Taipei, Taiwan, Republic of China

Keyword(s): Simulation System, Clustering, Decision Tree, Data Utilization.

Abstract: When designing public health policy to prevent the spread of disease, it is crucial to consider the difference in each administrative region. Residents’ daily and inter-regions activities are essential when epidemic diseases are spreading. Most of the statistical data in the traditional public health system cannot capture these behaviors. The standard statistic data and the disease transmission behaviors are combined and equally considered in the disease-transmission simulation system. According to the data from the simulation system, the administrative regions in Taiwan are separated into one urban and three non-urban areas by the clustering algorithm. Then we use decision tree algorithms to determine the main factors when deciding whether an area is rural or urban. The experiment results show that the percentage of elders and the road infrastructure is the main feature for determining the type of an area.

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Paper citation in several formats:
Lai, Z.; Chiang, Y.; Hsu, T. and Chang, H. (2022). Using Machine Learning Methods and the Influenza Simulation System to Explore the Similarities of Taiwan’s Administrative Regions. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-583-8; ISSN 2184-285X, SciTePress, pages 416-422. DOI: 10.5220/0011279100003269

@conference{data22,
author={Zong{-}Kai Lai. and Yi{-}Ting Chiang. and Tsan{-}sheng Hsu. and Hung{-}Jui Chang.},
title={Using Machine Learning Methods and the Influenza Simulation System to Explore the Similarities of Taiwan’s Administrative Regions},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA},
year={2022},
pages={416-422},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011279100003269},
isbn={978-989-758-583-8},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - DATA
TI - Using Machine Learning Methods and the Influenza Simulation System to Explore the Similarities of Taiwan’s Administrative Regions
SN - 978-989-758-583-8
IS - 2184-285X
AU - Lai, Z.
AU - Chiang, Y.
AU - Hsu, T.
AU - Chang, H.
PY - 2022
SP - 416
EP - 422
DO - 10.5220/0011279100003269
PB - SciTePress

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