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
Link To Document :
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