Application of Network Statistics Theory to Disaster and Disaster Prevention
| Project/Area Number |
16K00043
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Kanazawa University |
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Principal Investigator |
SAGAE MASAHIKO 金沢大学, 経済学経営学系, 教授 (20215669)
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| Co-Investigator(Kenkyū-buntansha) |
藤生 慎 金沢大学, 地球社会基盤学系, 准教授 (90708124)
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| Project Period (FY) |
2016-04-01 – 2022-03-31
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| Project Status |
Completed (Fiscal Year 2021)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 統計科学 / ノンパラメトリック / モバイル空間統計 / 国民健康保険 / 災害弱者 / ノンパラメトリック統計 / 国民健康保険データベース / ネットワークデータ / 到達圏解析 / 方向統計 / 大規模災害 / 国民健康保険DB / 方向統計学 / ネットワーク統計学 / カーネル関数 / 地震災害時の救援 / 災害・防災ネットワーク分析 / ビッグデータ解析 |
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| Outline of Final Research Achievements |
We have conducted research on pioneering network statistics and its application to disaster and disaster prevention network analysis. Specifically, the National Health Insurance Database (hereinafter referred to as KDB) The results of this research showed that it is possible to determine the evacuation priorities of citizens and the availability of evacuation assistance in response to information on diseases and nursing care retrieved from the National Health Insurance Database (KDB), and to analyze the vulnerable groups in the event of a disaster.
In addition, it was found that it is possible to assume the expected evacuation routes and areas that can be reached in the reachability area analysis. In addition, it was verified that the use of mobile spatial statistics can be used to predict the population currently staying in an assumed area, and that the mesh population at the time of evacuation can be used to estimate the expected population of evacuees, which is a basic analysis.
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| Academic Significance and Societal Importance of the Research Achievements |
下記のテーマを本研究で行った。①モバイル空間統計を用いた1時間単位の500ｍメッシュ人口の動的な動きを分析できる非負値行列分解法を開発した。②高齢者の年齢と歩行速度に基づいた到達圏解析で徒歩避難想定エリアの推定が可能となった。③モバイル空間統計にノンパラメトリック密度推定法を適用し、エリア内のリアルタイムの人口推計が可能となった。④KDBでエリア内の疾患の種別、障害の程度、高齢者の要介護者の有無、等のじょゆ法が抽出できた。
以上の①から④の成果を組み合わせることで災害時の避難所への災害弱者の避難計画や支援が可能となり、避難所別の想定される避難者の人数も推計可能となる。
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Report
(7 results)
Research Products
(62 results)
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[Journal Article] Analysis of Changes in Elderly People& Levels of Long-Term Care Needs and Related Factors With a Focus on Care Levels II and III2018
Author(s)
Yanagihara Kiyoko, Fujiu Makoto, Sano Shizuka, Takayama Junichi, Nishino Tatsuya, Tamamori Yuya, Sagae Masahiko , Samuta Hikaru, Hirako Kouhei, Sinohara Moeko and Tujiguti Hiromasa
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Journal Title
Journal of wellness and health care,
Volume: 41
Pages: 93-103
Related Report
Peer Reviewed
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