Optimization of the BP Neural Netwook with Particle Swarm Algorithm
Abstract：Most systemms are nonlinear in real life.Whether BP neural network could meet the local optimal value through training,whether it is comvergent and how long the training lasts are closely related to the initial value and the threshold value selected.This paper use a particle swarm algorithm with dynamic inertia weight network to optimize the initial value of the BP neural network.The experiment shows that the prediction error is very small when the particle swarm algorithm is used to optimize the BP neural network. Such an algorithm can jump out of local minimum value and get better results.
Keywords：particle swarm algorithmBP neural networkindividual extremumgroup extremum
Publication Date：2012-07-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：3( 254-255,270 )