Measurement of uranium quantities by fluorescence-X using neuronal techniques
Abstract
Layered neural networds are a class of models based on neural computation in biological systems. Connexionists models are made of a large number of simple computing structures, highly interconnectec. The weights assigned to the connections enable the encoding of the knowledge required for a task. They can be trained to learn any input-output relation after selecting a suitable architecture. This method appears useful in those cases in which a simple operation and a fast response are needed, together with a reasonnable accuracy. They are applied here to the automatic analysis of X-ray fluorescence spectra, obtained with plastic bottles irradiated by collimated beam of photons, emitted by a sealed source of iridium. The method could allow the surveillance of the measurement of uranium quantities in nuclear fuel cycles in processing plants.
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