%0 Journal Article
%A LI Wei-qiang
%A XU Jian-cheng
%A YIN Jian-feng
%T ee colony optimization algorithm for training feed-forward neural networks
%D 2009
%R 10.3778/j.issn.1002-8331.2009.24.014
%J Computer Engineering and Applications
%P 43-45
%V 45
%N 24
%X Training an artificial neural network is an optimization task since it is desired to find optimal weight set of a neural network in training process.Traditional training algorithms have some drawbacks such as getting in local minima and computational complexity.This paper introduces a kind use for training artificial feed-forward neural network based on Bee Colony Algorithm.Bee Colony Optimization algorithm is a simple，robust and population based stochastic optimization algorithm.The algorithm combines the exploration and exploitation processes effectively，and adopts a certain search strategy to skip from local optimization.The algorithm is successfully applied to XOR，N-Bit Parity and Encoder-Decoder problems，compared with the BP algorithm.Simulation results show that the proposed algorithm has better performance than the traditional GD algorithm and the LM algorithm.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009.24.014