WEKO3
アイテム
Automatic generation of an evaluation model of regional disaster prevention activities based on self-evaluation questionnaire
https://nied-repo.bosai.go.jp/records/5464
https://nied-repo.bosai.go.jp/records/54643d3f1d54-27f3-45e0-98b6-c7b1469b73d9
| Item type | researchmap(1) | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2025-05-05 | |||||||||||||||
| タイトル | ||||||||||||||||
| 言語 | en | |||||||||||||||
| タイトル | Automatic generation of an evaluation model of regional disaster prevention activities based on self-evaluation questionnaire | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
| 著者 |
Qinglin Cui
× Qinglin Cui
× Taiyoung Yi
× Kan Shimazaki
× Hitoshi Taguchi
× Yuichiro Usuda
|
|||||||||||||||
| 抄録 | ||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||
| 内容記述 | Regional disaster prevention activities must be evaluated in terms of their effectiveness and suitability, and then improved on the basis of this evaluation. Those who can evaluate such activities are required to have abundant on-site experience in and extensive knowledge on disaster prevention. However, there is a shortage of such talent, and the training and nurturing thereof requires considerable resources. To address these issues, machine learning was introduced in our previous study to automate the evaluation of such activities. In the present study, we propose the automatic generation of the evaluation model of such activities using the responses of a self-evaluation questionnaire as the input variables. The output variables are the results of a review committee consisting of experts on disaster prevention. This paper describes the application of the model to the fourth Disaster Prevention Map Contest, examines the predicted results, and discusses the application conditions and issues to be resolved. | |||||||||||||||
| 言語 | en | |||||||||||||||
| 書誌情報 |
en : Journal of Disaster Research 巻 13, 号 5, p. 886-896, 発行日 2018-10 |
|||||||||||||||
| ISSN | ||||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||||
| 収録物識別子 | 1883-8030 | |||||||||||||||
| DOI | ||||||||||||||||
| 関連識別子 | 10.20965/jdr.2018.p0886 | |||||||||||||||
