Title :
Study on the Identification of Loading Materials for Initiating Explosive Device
Author :
Wang, Yong ; Li, Jianfu
Author_Institution :
Dept. of Comput., Chongqing Educ. Coll.
Abstract :
Neural network (NN) design is a key issue in the study of artificial neural networks. The use of genetic algorithm in searching the best hidden neurons makes the structural modular neural network less likely to be trapped in local minima than the traditional gradient-based search algorithms. Based on the analyses of the pressing model of loading materials for initiating explosive device and the cooperation of computing intelligent theories, an identification system of loading materials for initiating explosive device is developed on neural networks with genetic algorithms. Emphatically the experiment results show the identification requirement of loading materials for initiating explosive device can be satisfied in this system
Keywords :
explosives; genetic algorithms; neural nets; search problems; artificial neural networks; explosive device; genetic algorithm; gradient-based search algorithms; loading materials identification; Algorithm design and analysis; Artificial neural networks; Computer networks; Explosives; Genetic algorithms; Intelligent networks; Load modeling; Neural networks; Neurons; Pressing;
Conference_Titel :
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7803-9584-0
Electronic_ISBN :
0-7803-9585-9
DOI :
10.1109/ICCCAS.2006.285076