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Inversion of self-potential anomalies caused by simple-geometry bodies using global optimization algorithms

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dc.creator Gokturkler, G.
dc.creator BALKAYA, Çağlayan
dc.date 2012-09-30T21:00:00Z
dc.date.accessioned 2020-10-06T09:50:16Z
dc.date.available 2020-10-06T09:50:16Z
dc.identifier 4dc6add7-d582-4483-9348-e708cd42b974
dc.identifier 10.1088/1742-2132/9/5/498
dc.identifier https://avesis.sdu.edu.tr/publication/details/4dc6add7-d582-4483-9348-e708cd42b974/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/59684
dc.description Three naturally inspired meta-heuristic algorithms-the genetic algorithm (GA), simulated annealing (SA) and particle swarm optimization (PSO)-were used to invert some of the self-potential (SP) anomalies originated by some polarized bodies with simple geometries. Both synthetic and field data sets were considered. The tests with the synthetic data comprised of the solutions with both noise-free and noisy data; in the tests with the field data some SP anomalies observed over a copper belt (India), graphite deposits (Germany) and metallic sulfide (Turkey) were inverted. The model parameters included the electric dipole moment, polarization angle, depth, shape factor and origin of the anomaly. The estimated parameters were compared with those from previous studies using various optimization algorithms, mainly least-squares approaches, on the same data sets. During the test studies the solutions by GA, PSO and SA were characterized as being consistent with each other; a good starting model was not a requirement to reach the global minimum. It can be concluded that the global optimization algorithms considered in this study were able to yield compatible solutions with those from widely used local optimization algorithms.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Inversion of self-potential anomalies caused by simple-geometry bodies using global optimization algorithms
dc.type info:eu-repo/semantics/article


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