Abstract
A genetic algorithm was implemented for finding an
approximative solution to the problem of fitting a
combination of Lorentzian lines to a measured Mossbauer
spectrum. This iterative algorithm exploits the idea of
letting several solutions (individuals) compete with
each other for the opportunity of being selected to
create new solutions (reproduction). Each solution was
represend as a string of binary digits (chromossome).
In addition, the bits in the new solutions may be
switched randomly from zero to one or conversely
(mutation). The input of the program that implements
the genetic algorithm consists of the measured
spectrum, the maximum velocity, the peak positions and
the expected number of Lorentzian lines in the
spectrum. Each line is represented with the help of
three variables, which correspond to its intensity,
full line width at hald maxima and peak position. An
additional parameter was associated to the background
level in the spectrum. A chi-2 test was used for
determining the quality of each parameter combination
(fitness). The results obtained seem to be very
promising and encourage to further development of the
algorithm and its implementation.
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