Fuzzy identification of γ ray fingerprints based on adaptive network-based fuzzy inference system

Abstract

An identification method of γ-ray fingerprints based on adaptive network-based fuzzy inference system is brought forward. By setting up model and performing simulation, the parameters of the system relevant to the γ-ray fingerprints are extracted as the identification features. The two-dimensional fuzzy set about the identification features is put forward, and the fundamental principle for identification is established. The types and the individuals of nuclear materials are identified successfully with high degree of confidence. The simulation materials as radiation sources are identified with the method, and the performance of the method is studied and discussed. The results show that the method has not only strong capabilities for identifying the types and the individuals of the radiation sources, but also strong de-noising capability and low identification limit, and it can be applied to the nuclear materials safeguard.