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Application of particle swarm optimization in optimal placement of tsunami sensors

Rapid detection and early warning systems demonstrate crucial significance in tsunami risk reduction measures. So far, several tsunami observation networks have been deployed in tsunamigenic regions to issue effective local response. However, guidance on where to station these sensors are limited. I...

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Autores principales: Ferrolino, Angelie, Mendoza, Renier, Magdalena, Ikha, Lope, Jose Ernie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924491/
https://www.ncbi.nlm.nih.gov/pubmed/33816981
http://dx.doi.org/10.7717/peerj-cs.333
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author Ferrolino, Angelie
Mendoza, Renier
Magdalena, Ikha
Lope, Jose Ernie
author_facet Ferrolino, Angelie
Mendoza, Renier
Magdalena, Ikha
Lope, Jose Ernie
author_sort Ferrolino, Angelie
collection PubMed
description Rapid detection and early warning systems demonstrate crucial significance in tsunami risk reduction measures. So far, several tsunami observation networks have been deployed in tsunamigenic regions to issue effective local response. However, guidance on where to station these sensors are limited. In this article, we address the problem of determining the placement of tsunami sensors with the least possible tsunami detection time. We use the solutions of the 2D nonlinear shallow water equations to compute the wave travel time. The optimization problem is solved by implementing the particle swarm optimization algorithm. We apply our model to a simple test problem with varying depths. We also use our proposed method to determine the placement of sensors for early tsunami detection in Cotabato Trench, Philippines.
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spelling pubmed-79244912021-04-02 Application of particle swarm optimization in optimal placement of tsunami sensors Ferrolino, Angelie Mendoza, Renier Magdalena, Ikha Lope, Jose Ernie PeerJ Comput Sci Optimization Theory and Computation Rapid detection and early warning systems demonstrate crucial significance in tsunami risk reduction measures. So far, several tsunami observation networks have been deployed in tsunamigenic regions to issue effective local response. However, guidance on where to station these sensors are limited. In this article, we address the problem of determining the placement of tsunami sensors with the least possible tsunami detection time. We use the solutions of the 2D nonlinear shallow water equations to compute the wave travel time. The optimization problem is solved by implementing the particle swarm optimization algorithm. We apply our model to a simple test problem with varying depths. We also use our proposed method to determine the placement of sensors for early tsunami detection in Cotabato Trench, Philippines. PeerJ Inc. 2020-12-18 /pmc/articles/PMC7924491/ /pubmed/33816981 http://dx.doi.org/10.7717/peerj-cs.333 Text en © 2020 Ferrolino et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Optimization Theory and Computation
Ferrolino, Angelie
Mendoza, Renier
Magdalena, Ikha
Lope, Jose Ernie
Application of particle swarm optimization in optimal placement of tsunami sensors
title Application of particle swarm optimization in optimal placement of tsunami sensors
title_full Application of particle swarm optimization in optimal placement of tsunami sensors
title_fullStr Application of particle swarm optimization in optimal placement of tsunami sensors
title_full_unstemmed Application of particle swarm optimization in optimal placement of tsunami sensors
title_short Application of particle swarm optimization in optimal placement of tsunami sensors
title_sort application of particle swarm optimization in optimal placement of tsunami sensors
topic Optimization Theory and Computation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924491/
https://www.ncbi.nlm.nih.gov/pubmed/33816981
http://dx.doi.org/10.7717/peerj-cs.333
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