Personally Collected Various Intelligent Algorithms with Source Code

My personal collection of intelligent algorithms is quite comprehensive, containing more than 20 distinct source code implementations. These algorithms include but are not limited to: Genetic Algorithm (with roulette wheel selection and crossover operations), Ant Colony Optimization (featuring pheromone update mechanisms), Particle Swarm Optimization (with velocity and position update equations), Differential Evolution (utilizing mutation and recombination operations), along with hybrid algorithms such as Genetic-Neural Network (combining GA for feature selection with neural network training), PSO-SVM (using particle swarm for SVM parameter optimization), and PSO-Neural Network (applying PSO to optimize neural network weights). Each algorithm demonstrates unique characteristics and optimization methodologies suitable for various problem domains, providing extensive options for solving complex computational challenges. The source codes have been carefully collected and organized to ensure quality and reliability, featuring clear code structures and parameter configuration examples. For those interested in these algorithms, I can share additional implementation details and sample code demonstrations including specific function descriptions and parameter tuning guidelines.