PSOt Particle Swarm Optimization Toolbox

This is a highly practical Particle Swarm Optimization (PSO) toolbox designed for researchers and developers working with artificial intelligence, neural networks, and deep learning. The toolbox provides comprehensive functionality and algorithms to solve various optimization problems, featuring customizable swarm size, iteration parameters, and convergence criteria. Key implementations include velocity updates using inertia weights, personal-best and global-best position tracking, and boundary constraint handling mechanisms. Users can leverage this toolbox for hyperparameter tuning in neural networks, feature selection optimization, or other AI-related optimization tasks. The modular architecture allows easy integration with existing MATLAB/Simulink workflows while supporting custom objective functions through standardized interface design. If you're interested in particle swarm optimization algorithms, you can download and utilize this toolbox directly. We hope this tool proves valuable for your research and learning endeavors!