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Evolutionary Applications to Cellular Automata Models for Volcano Risk Mitigation

  • Giuseppe Filippone
  • Roberto Parise
  • Davide Spataro
  • Donato D’Ambrosio
  • Rocco Rongo
  • William Spataro
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 445)

Abstract

A GPGPU accelerated evolutionary computation-based decision support system for defining and optimizing volcanic hazard mitigation interventions is proposed. Specifically, the new Cellular Automata numerical model SCIARA-fv3 for simulating lava flows at Mt Etna (Italy) and Parallel Genetic Algorithms (PGA) have been applied for optimizing protective measures construction by morphological evolution. A case study is considered, where PGA are applied for the optimization of the position, orientation and extension of earth barriers built to protect a touristic facility located near the summit of Mt. Etna (Italy) volcano which was interested by the 2001 lava eruption. The methodology has produced extremely positive results and, in our opinion, can be applied within a broader risk assessment framework, having immediate and far reaching implications both in land use and civil defense planning.

Keywords

Evolutionary computation Parallel genetic algorithms Decision support system Cellular automata Morphological evolution 

Notes

Acknowledgments

This work was partially funded by the European Commission \(-\) European Social Fund and by the Regione Calabria (Italy). Authors gratefully acknowledge the support of NVIDIA Corporation for this research.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Giuseppe Filippone
    • 1
  • Roberto Parise
    • 1
  • Davide Spataro
    • 1
  • Donato D’Ambrosio
    • 1
    • 2
  • Rocco Rongo
    • 1
    • 2
  • William Spataro
    • 1
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of CalabriaRendeItaly
  2. 2.CNR-IRPI, Sezione di CosenzaRendeItaly

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