Computer and Modernization

Previous Articles     Next Articles

 BP Neural Network Algorithm Based on Frog Leaping Particle Swarm Optimization

  

  1. 1. Information Engineering Institute， China University of Geosciences， Beijing 100083， China；

     2. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083， China
  • Received:2015-07-13 Online:2015-09-21 Published:2015-09-24

Abstract:

In order to solve the problems that the calculation of BP neural network is very complex and its convergence rate is slow， an iterative method of weight and
threshold of the BP neural network based on the heuristic algorithm is put forward. This method combined with two advantages of the Frog Leaping Particle Swarm, in which, one is
less controllable parameter than normal ways and the other one is the fast convergence speed. In essence, the weight and the threshold of neural network can be seen as
particles. BP neural network was trained by particle updating and the accuracy of the algorithm is about 1.5342e-03.

Key words: shuffled frog leaping algorithm, particle swarm optimization algorithm, BP neural network