Computational modeling of thermoluminescence glow curves of zinc borate crystals

Abstract

This work presents a new approach based on multilayered perceptrons (MLPs) to compute the thermoluminescence glow curves in undoped and La-doped zinc borate crystals. The MLP has been trained by a genetic algorithm (GA) and a Levenberg-Marquardt learning algorithm. The results obtained using the MLP models were tested with untrained experimental glow curve data. The comparison has shown that the proposed model can predict more accurately and easily the thermoluminescence glow curves.