A disaster response model driven by spatial-temporal forecasts

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

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Dangosydd eitem ddigidol (DOI)

  • Kostas Nikolopoulos
  • Fotios Petropoulos
    University of Bath
  • Vasco Sanchez Rodrigues
    School of Healthcare Sciences, Cardiff University
  • Stephen Pettit
    School of Healthcare Sciences, Cardiff University
  • Anthony Beresford
    School of Healthcare Sciences, Cardiff University
In this research, we propose a disaster response model combining preparedness and responsiveness strategies. The selective response depends on the level of accuracy that our forecasting models can achieve. In order to decide the right geographical space and time window of response, forecasts are prepared and assessed through a spatial-temporal aggregation framework, until we find the optimum level of aggregation. The research considers major earthquake data for the period 1985 – 2014. Building on the produced forecasts, we develop accordingly a disaster response model. The model is dynamic in nature, as it is updated every time a new event is added in the database. Any forecasting model can be optimized though the proposed spatial-temporal forecasting framework, and as such our results can be easily generalized. This is true for both other forecasting methods, as well as in other disaster response contexts.
Iaith wreiddiolSaesneg
Tudalennau (o-i)1214-1220
CyfnodolynInternational Journal of Forecasting
Cyfrol38
Rhif y cyfnodolyn3
Dyddiad ar-lein cynnar14 Chwef 2020
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - Gorff 2022

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