Recent development of Laser–Induced Breakdown Spectroscopy (LIBS) caused that this method is considered as the
most promising for future diagnostic applications for characterization of the deposited materials in the International
Thermonuclear Experimental Reactor (ITER), which is currently under construction. In this article the basics of LIBS are
shortly discussed and the software for spectra analyzing is presented. The main software function is to analyze measured
spectra with respect to the certain element lines presence. Some program operation results are presented. Correct results
for graphite and aluminum are obtained although identification of tungsten lines is a problem. The reason for this is low
tungsten lines intensity, and thus low signal to noise ratio of the measured signal. In the second part artificial neural
networks (ANNs) as the next step for LIBS spectra analyzing are proposed. The idea is focused on multilayer perceptron
network (MLP) with backpropagation learning method. The potential of ANNs for data processing was proved through
application in several LIBS–related domains, e.g. differentiating ancient Greek ceramics (discussed). The idea is to apply
an ANN for determination of W, Al, C presence on ITER–like plasma–facing materials.
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