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An unconventional solution for finding the location of event creation ispresented. It is based on two feed-forward neural networks with fixedarchitecture, whose parameters are chosen so as to reach a high accuracy. Theinteraction point location is a parameter that can be used to select events ofinterest from the very high rate of events created at the current experimentsin High Energy Physics. The system suggested here is tested on simulated datasets of the ZEUS Central Tracking Detector, and is shown to perform better thanconventional algorithms.Comment: Presentes at ACAT 2000, FermiLab, Chicago, October 200

Vertex reconstructing neural network at the ZEUS central tracking detector