2005, Volume 7, Issue 5
Strategic Study of CAE >> 2005, Volume 7, Issue 5
An Improving Method of BP Neural Network and Its Application
Missile Institute , Air Force Engineering University , Sanyuan , Shanxi 713800 , China
Next Previous
Abstract
Seeing on that in BPNN the small learning gene will make the long training time, but the large learning gene will make the BPNN surging, this paper brings forward a way to modify the learning gene, that is, adding a proportion gene before the learning gene, The proportion gene will change when the weight of the BPNN needs to be modified. This can shorten the training time and make convergence better as well. The simulating results show that the new algorithm is much better than the old one during BPNN scouting the missile command.
Keywords
Figures
图1
图2
图3
图4
References
[ 1 ] ZhangGP.Neuralnetworksforclassification:a survey[J].IEEETransonSestems, Man, and Cybernetics—PartC:ApplicationsandReviews, 2000, 30 (4) :451～462
[ 2 ] 刘兴堂.应用自适应控制[M].西安:西北工业大学出版社, 2003 link1
[ 3 ] 顾军华, 等.基于改进BP神经网络的税收收入预测模型[J].河北工业大学学报, 2003, (1) :39～43 link1
[ 4 ] 景韶光, 陈新海.非线性神经网络自适应控制及其在导弹中的应用[J].西北工业大学学报, 1997, (4) :603～606 link1
京公网安备 11010502051620号
