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Investigation Of The Efficiency Of Genetic Algorithms For Solving Large-Scale Geophysical Problems: Examples From Mt And Dc Data Inversion
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 9th Congress of the Balkan Geophysical Society, Nov 2017, Volume 2017, p.1 - 5
Abstract
Global search algorithms, particularly genetic algorithms (GA) are gaining more popularity in the area of geophysical parameter estimation. This group of search and optimization algorithm mimics an optimized natural process to minimize an objective function. The parameters are not inverted from the measured data; instead, they are verified via a misfit/fitness function. The size of the search space for a given problem depends on the number of free parameters and the search interval assigned to each parameter. This paper investigates how large problems can be evaluated using genetic algorithms. It is obvious that without any physical or geometric constraints on two or three dimensional models genetic algorithms may become useless and infeasible. This aspect is discussed on two dimensional problems from dc resistivity and magnetotelluric methods.