Open AccessOptimization of Radiation Model of Infrared Decoy with Neural Network
Author(s) -
Guanwu Zhou
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1302/4/042027
Subject(s) - decoy , artificial neural network , computer science , infrared , radiation , backpropagation , algorithm , artificial intelligence , physics , optics , chemistry , biochemistry , receptor
In this paper, a numerical model is proposed to calculate the infrared radiation characteristics based on the solution of radioactive transport. However, due to the demand of the real-time, a method with back-propagation neural network (BPNN) is developed to optimize the proposed model. The results of simulation experiments show that BPNN possesses good prediction accuracy, and can make the numerical model achieve the real-time requirement.