pso Resources

Showing items tagged with "pso"

Implementation of PSO-optimized PID controller design using Simulink environment, where PID_Model represents the control system model, PSO module handles particle swarm optimization algorithms, and PSO_PID implements the parameter optimization process for PID controllers through iterative swarm intelligence techniques.

MATLAB 215 views Tagged

A comprehensive PSO program package consisting of three core files: DeJong.m (fitness function), get_psoOptions.m (configuration settings), and pso.m (main algorithm). Simply copy these files to your MATLAB work directory for immediate execution. Customize parameters through get_psoOptions.m and modify the objective function in DeJong.m to adapt the algorithm to specific optimization problems.

MATLAB 252 views Tagged

Particle Swarm Optimization (PSO) is an evolutionary computation technique co-invented by Dr. Eberhart and Dr. Kennedy. Inspired by studies of bird flock predation behavior, PSO is similar to Genetic Algorithms as an iteration-based optimization tool. Implementation typically involves initializing particle positions/velocities, updating particle velocities based on personal and global best positions using inertia weights, and iteratively converging toward optimal solutions through social learning mechanisms.

MATLAB 218 views Tagged

Implementation of feature selection techniques for SVR machine learning algorithms, featuring one filter-based method (CFS Correlation-based Feature Selection) and two wrapper methods (Genetic Algorithm GA and Particle Swarm Optimization PSO). The gridsearch module performs hyperparameter tuning for SVR optimization, while SVM_CV handles k-fold cross-validation procedures with customizable parameters.

MATLAB 310 views Tagged