DocumentCode
1837784
Title
New evolutionary neural networks
Author
Gao, Wei
Author_Institution
Wuhan Polytech. Univ., China
fYear
2005
fDate
26-28 May 2005
Firstpage
167
Lastpage
171
Abstract
The evolutionary neural network can be generated combining the evolutionary computation and neural network. Based on analysis of merits and demerits of previously proposed evolutionary neural network models, combining the immunized evolutionary programming proposed by author and BP neural network, a new evolutionary neural network model whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new model is compared and analyzed with BP neural network and traditional evolutionary neural network. The computing results show that the precision and efficiency of the new model are all good.
Keywords
backpropagation; evolutionary computation; neural nets; XOR problem; connection weights; evolutionary computation; evolutionary neural network; immunized evolutionary programming; neural network architecture; Algorithm design and analysis; Competitive intelligence; Computer architecture; Computer networks; Evolutionary computation; Genetic algorithms; Genetic programming; Intelligent networks; Neural networks; Next generation networking;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Interface and Control, 2005. Proceedings. 2005 First International Conference on
Print_ISBN
0-7803-8902-6
Type
conf
DOI
10.1109/ICNIC.2005.1499869
Filename
1499869
Link To Document