A Novel Back-propagation Neural Network Training Algorithm Designed by an Ant Colony Optimization

@article{Li2005ANB,
  title={A Novel Back-propagation Neural Network Training Algorithm Designed by an Ant Colony Optimization},
  author={Jeng-Bin Li and Yun-Kung Chung},
  journal={2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific},
  year={2005},
  pages={1-5}
}
This article presents a new back-propagation neural network (BPN) training algorithm performed with an ant colony optimization (ACO) to get the optimal connection weights of the BPN. The concentration of pheromone laid by the artificial ants moving on the connection path is the key factor of the optimal weight determination. This is the metaphor that the optimal weights make the "total length of neuron-to-neuron connections traversed by all artificial ants," which is defined by the BPN output… CONTINUE READING
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