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  1. 防災科研関係論文

機械学習を用いた地域防災活動の評価モデルの自動生成方法に関する研究

https://nied-repo.bosai.go.jp/records/4872
https://nied-repo.bosai.go.jp/records/4872
b97b6ce6-18f6-4ae7-ad80-259f3ecfa648
Item type researchmap(1)
公開日 2025-03-17
タイトル
言語 ja
タイトル 機械学習を用いた地域防災活動の評価モデルの自動生成方法に関する研究
タイトル
言語 en
タイトル Automatic Performing Method of Regional Disaster Prevention Activities Evaluation Model Using Machine Learning
言語
言語 jpn
著者 崔 青林

× 崔 青林

ja 崔 青林

en CUI Qinglin

Search repository
島崎 敢

× 島崎 敢

ja 島崎 敢

en SHIMAZAKI Kan

Search repository
李 泰榮

× 李 泰榮

ja 李 泰榮

en YI Taiyoung

Search repository
臼田 裕一郎

× 臼田 裕一郎

ja 臼田 裕一郎

en USUDA Yuichiro

Search repository
抄録
内容記述タイプ Other
内容記述 <p>In order to conduct regional disaster prevention activities continuously and appropriately, it is necessary to evaluate the effectiveness and appropriateness, and make the improvements based on evaluation. However, there are insufficient human resources of evaluators and it is difficult to foster the talent, since extensive field experience and broad disaster prevention knowledge is required for appropriate evaluation. This study constructed a prototype of a machine learning system for automatically evaluating regional disaster prevention activities. It also performs the machine learning with the data from activity records of the Bosai Contest as input variables, and the winning judgment data evaluated by the expert's review committee as output variables. As a result, the same result as experts' judgment was obtained with the probability of 94% for learning data and 79% for verification data.</p>
言語 ja
抄録
内容記述タイプ Other
内容記述 <p>In order to conduct regional disaster prevention activities continuously and appropriately, it is necessary to evaluate the effectiveness and appropriateness, and make the improvements based on evaluation. However, there are insufficient human resources of evaluators and it is difficult to foster the talent, since extensive field experience and broad disaster prevention knowledge is required for appropriate evaluation. This study constructed a prototype of a machine learning system for automatically evaluating regional disaster prevention activities. It also performs the machine learning with the data from activity records of the Bosai Contest as input variables, and the winning judgment data evaluated by the expert's review committee as output variables. As a result, the same result as experts' judgment was obtained with the probability of 94% for learning data and 79% for verification data.</p><p></p>
言語 en
書誌情報 ja : 地域安全学会論文集
en : Journal of Social Safety Science

巻 31, 号 0, p. 271-277, 発行日 2017
出版者
言語 ja
出版者 一般社団法人 地域安全学会
出版者
言語 en
出版者 Institute of Social Safety Science
ISSN
収録物識別子タイプ ISSN
収録物識別子 1345-2088
DOI
関連識別子 10.11314/jisss.31.271
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