Particle Swarm Optimization Algorithm for RBF Neural Network Enhancement

PSO-based RBFNN Optimization Algorithm Steps: 1. Normalize sample data by scaling inputs/outputs to [-1,1] range; 2. Determine RBF network centers and widths; 3. Use PSO algorithm with root mean square fitting error as performance metric to optimize connection weight matrix between RBF network output and hidden layers