Application of particle swarm optimization in optimal placement of tsunami sensors.
Finite volume method
Heuristic algorithm
Nonlinear shallow water equations
Particle swarm optimization
Tsunami early warning system
Tsunami sensors
Journal
PeerJ. Computer science
ISSN: 2376-5992
Titre abrégé: PeerJ Comput Sci
Pays: United States
ID NLM: 101660598
Informations de publication
Date de publication:
2020
2020
Historique:
received:
07
08
2020
accepted:
18
11
2020
entrez:
5
4
2021
pubmed:
6
4
2021
medline:
6
4
2021
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 33816981
doi: 10.7717/peerj-cs.333
pii: cs-333
pmc: PMC7924491
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e333Informations de copyright
© 2020 Ferrolino et al.
Déclaration de conflit d'intérêts
The authors declare that they have no competing interests.
Références
PLoS One. 2017 Mar 10;12(3):e0172583
pubmed: 28282428