Proceedings PaperDecision making using conventional calculations versus neural networks for substance identification
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Neural network calculations are compared to conventional probability calculations for decision making in an explosives detection system. The explosives detection system, which has been tested in the laboratory, is a pulsed fast neutron spectrometer that measures the attenuation of neutrons for a particular suitcase loading. The attenuation curves along with the measured total cross sections are used to determine the amount of hydrogen, carbon, nitrogen and oxygen in volume increments through the suitcase. This information is used to determine a probability of detection (of explosives) versus a probability of false alarm curve. The same information is used in a neural network program to determine its effectiveness in predicting the presence of explosives. The neural network was trained from computer generated data and tested on extrapolated laboratory data.