Application of particle swarm optimization in optimal placement of tsunami sensors

PeerJ Comput Sci. 2020 Dec 18:6:e333. doi: 10.7717/peerj-cs.333. eCollection 2020.

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.

Keywords: Finite volume method; Heuristic algorithm; Nonlinear shallow water equations; Particle swarm optimization; Tsunami early warning system; Tsunami sensors.

Grants and funding

This work was funded by the UP System Enhanced Creative Work and Research Grant (ECWRG-2019-2-11-R) and the Research Grant from Institut Teknologi Bandung. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.