Abstract

A new method for inversion of surface-wave dispersion data is introduced. This method successfully utilizes recently developed genetic algorithms as a global optimization method. Such algorithms usually consist of selection, crossover, and mutation of individuals in a population. To facilitate convergence to an optimal solution, we added elite selection, which ensures that the ``best'' individual with the smallest misfit value is not excluded from the succeeding generation, and dynamic mutation, which contains a generation-variant mutation probability. Using synthetic and observed earthquake data, we examined the applicability of this genetic surface-wave inversion method in deducing an S-wave profile for sedimentary layers from short- and intermediate-period surface-wave dispersion data. We demonstrated that the method is robust and can be used to interpret surface-wave dispersion data.

Return to Table of Contents