DocumentCode
2021127
Title
Evolutionary Neural Network Based on New Ant Colony Algorithm
Author
Wei Gao
Author_Institution
Wuhan Polytech. Univ., Wuhan
Volume
1
fYear
2008
fDate
17-18 Oct. 2008
Firstpage
318
Lastpage
321
Abstract
The evolutionary neural network is the combination of the evolutionary optimization algorithm and traditional neural network. To overcome the demerits of previously proposed evolutionary neural networks, combining the immune continuous ant colony algorithm proposed by author and BP neural network, a new evolutionary neural network whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new evolutionary neural network is compared and analyzed with BP neural network, traditional evolutionary neural network based on genetic algorithm and evolutionary neural network based on evolutionary programming. The computing results show that the precision and efficiency of the new evolutionary neural network are all the best.
Keywords
artificial immune systems; backpropagation; genetic algorithms; neural nets; BP neural network; artificial intelligence; evolutionary neural network; evolutionary programming; genetic algorithm; immune continuous ant colony algorithm; Algorithm design and analysis; Ant colony optimization; Evolutionary computation; Feedforward neural networks; Feeds; Flowcharts; Genetic algorithms; Genetic programming; Neural networks; Optimization methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3311-7
Type
conf
DOI
10.1109/ISCID.2008.143
Filename
4725617
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