Neural networks learning using VBEST model particle swarm optimisation
Hongbo Liu, Yi‐Yuan Tang, Jun Meng, Ye Ji · 2005
The two most commonly used methods are known as gbest model and lbest model in particle swarm optimization (PSO). The gbest model converges quickly on problem solutions but has a weakness of becoming trapped in local optima, while the lbest model is able to "flow around" local optima, as the individuals explore different regions. In this paper, we investigated a variable neighborhood model in particle swarm search method for neural network learning, and the experimental results illustrated its efficiency.