This paper is concerned with the possibilities of computational intelligence
application for simultaneous determination of the laser beam spatial profile
and vibrational-to-translational relaxation time of the polyatomic molecules
in gases by pulsed photoacoustics. Results regarding the application of
neural computing and genetic optimization are presented through the use of
feed forward multilayer perception networks and real-coded genetic
algorithms. Feed forward multilayer perception networks are trained in an
offline batch training regime to estimate simultaneously, and in real-time,
laser beam spatial profile R(r) (profile shape class) and
vibrational-to-translational relaxation time ?V?T from a given (theoretical)
photoacoustic signals ?p(r,t). The proposed method significantly shortens the
time required for the simultaneous determination of the laser beam spatial
profile and relaxation time and has the advantage of accurately calculating
the aforementioned quantities. Real coded genetic algorithms are used to
calculate ?V?T by fitting the ?p(r,t) with the theoretical one. The
previously developed methods determine the laser beam profile and relaxation
time with sufficient precision, but the methods based on the application of
artificial intelligence are more suitable for practical applications, such as
the real-time in-situ measurements of atmospheric pollutants.
Computational intelligence based simultaneous determination of the spatial profile of the laser beam and vibrational-to-translational relaxation time by pulsed photoacoustics
