Articles | Volume 22, issue 6
Nat. Hazards Earth Syst. Sci., 22, 2131–2144, 2022
https://doi.org/10.5194/nhess-22-2131-2022
Nat. Hazards Earth Syst. Sci., 22, 2131–2144, 2022
https://doi.org/10.5194/nhess-22-2131-2022
Research article
24 Jun 2022
Research article | 24 Jun 2022

Strategic framework for natural disaster risk mitigation using deep learning and cost-benefit analysis

Ji-Myong Kim et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-294', Anonymous Referee #1, 21 Nov 2021
    • AC1: 'Reply on RC1', Sang-Guk Yum, 18 Mar 2022
  • RC2: 'Comment on nhess-2021-294', Anonymous Referee #2, 11 Mar 2022
    • AC2: 'Reply on RC2', Sang-Guk Yum, 18 Mar 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (19 Mar 2022) by Vassiliki Kotroni
AR by Sang-Guk Yum on behalf of the Authors (24 Mar 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (29 Apr 2022) by Vassiliki Kotroni
RR by Anonymous Referee #2 (24 May 2022)
ED: Publish as is (01 Jun 2022) by Vassiliki Kotroni
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Short summary
Insurance data has been utilized with deep learning techniques to predict natural disaster damage losses in South Korea.
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