Title :
Study on Evolutionary Neural Network Based on Ant Colony Optimization
Author_Institution :
Wuhan Polytech. Univ., Wuhan
Abstract :
The evolutionary neural network model can be generated combining the evolutionary optimization algorithm and neural network. Based on analysis of merits and demerits of previously proposed evolutionary neural network models, combining the continuous ant colony optimization 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 ENN is compared and analyzed with BP neural network, traditional ENN based on genetic algorithm and evolutionary programming. The computing results show that the precision and efficiency of the new ENN are all better.
Keywords :
backpropagation; evolutionary computation; neural nets; BP neural network; XOR problem; ant colony optimization; evolutionary neural network; evolutionary optimization algorithm; evolutionary programming; genetic algorithm; Algorithm design and analysis; Ant colony optimization; Computational intelligence; Evolutionary computation; Feedforward neural networks; Feeds; Genetic algorithms; Genetic programming; Neural networks; Performance analysis;
Conference_Titel :
Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3073-4
DOI :
10.1109/CISW.2007.4425432