Title :
Weapon systematic safety evaluation model based on genetic algorithm and BP neural network
Author :
Kai, Cheng ; Hong-jun, Zhang ; Bo, Xu ; Li-li, Shan
Author_Institution :
Eng. Inst. of Corps of Eng., PLA Univ. of Sci. & Technol., Nanjing, China
Abstract :
The traditional neural network is unavoidable to present local extreme value question, may result in failing training. On the basis of quantization of weapon system safe index, it has adopted neural network based on improved genetic algorithm to set up the systematic safety evaluation model of the weapon. It utilizes improved genetic algorithm to optimize the weight of neural network and get the final assessment value through twice training of neural network. The simulation result implies that the convergence speed of hybrid algorithm is quick and it can avoid local extreme value question effectively.
Keywords :
backpropagation; genetic algorithms; learning (artificial intelligence); military computing; safety; weapons; BP neural network; genetic algorithm; hybrid algorithm; weapon system safe index; weapon systematic safety evaluation model; Artificial neural networks; Encoding; Gallium; Genetic algorithms; Neurons; Training; Weapons;
Conference_Titel :
Information Science and Technology (ICIST), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9440-8
DOI :
10.1109/ICIST.2011.5765108