Title :
Operational ability evaluation model of the armored weapon system of system
Author :
Zuo Xuesheng ; Qu Yang
Author_Institution :
Armored Inst., Bengbu, China
Abstract :
On the basis of taking the weapon system of system operational ability evaluation indexes for reference, we combine with the character of the armored weapon , seek advice from experts, and built the armored weapon operational ability evaluation indexes system. Then, we take the building train samples and experts marking samples to train the BP neural networks, and evaluate the armored weapon system of system operational ability. The results indicate the trained neural network is reasonable to evaluate the operational ability. It could reduce the artificial factor, and make the results more reliable. The model could take reference for the operational evaluation to the armored weapon system of system.
Keywords :
armour; backpropagation; military computing; neural nets; weapons; BP neural network; armored weapon system of system; artificial factor; building train sample; experts marking sample; operational ability evaluation model; system operational ability evaluation index; trained neural network; Biological neural networks; Indexes; Modeling; Training; Weapons; Armored weapon SOS; Evaluation; Neural Network; Operational Ability;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561293