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Application of particle swarm optimization in optimal placement of tsunami sensors.

ABSTRACT: 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.

SUBMITTER: Ferrolino A

PROVIDER: S-EPMC7924491 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Application of particle swarm optimization in optimal placement of tsunami sensors.

Ferrolino Angelie A Mendoza Renier R Magdalena Ikha I Lope Jose Ernie JE

PeerJ. Computer science 20201218

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 ...[more]

PMID: 33816981

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