Use of Pso Algorithm in Determination of the Optimum Observation Weights in the Deformation Monitoring Networks (original) (raw)

2012, ERJ. Engineering Research Journal

Geodetic networks are very important tools used to monitor earth and/or structural deformations. However, a geodetic network must be designed to meet sufficiently some network quality requirements such as precision, reliability, or sensitivity. This is the subject of geodetic network optimization. The determination of the observation weights problem in the deformation monitoring networks can be dealt with as an optimization procedure, this problem can performed by solving the second-order design (SOD) problem. Traditional methods have been used for geodetic optimization tasks. On the other hand, some heuristic techniques have been started to be used recently in geodetic science such as the Particle Swarm Optimization (PSO) algorithm. The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much attention in past years, with many attempts to find the variant that performs best on a wide variety of optimization problems. In this paper, the PSO algorithm, a stochastic global optimization method, has been employed for the determination of the optimum observation weights to be measured in the field that will meet the postulated criterion matrix at a reasonable precision. The fundamentals of the method and a numeric example are given.

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