Professional MATLAB source code with comprehensive documentation and examples
Standard BP neural network algorithm implementation featuring momentum BP algorithm and PSO-optimized neural network using TRAINGDX training method. The code includes neural network training routines with gradient descent optimization techniques.
Neural Network Toolbox featuring SVM and NPA algorithms, including "one-against-all" and "one-against-one" classification methods with extensive practical examples and code demonstrations.
Parameter optimization, classification prediction, and regression prediction with information granulation, implemented through machine learning algorithms.
Memetic cultural evolution is an efficient computational optimization approach demonstrated using Rosenbrock function as an example case study. Users can extend the implementation by adding other benchmark functions for comparative testing and valida
BP Neural Network Prediction Program - The second data point in the first row represents the hourly water consumption at 2:00 AM on the day before the prediction date, corresponding to the second data point in train_flowoutput's first row. The second
Shared genetic algorithm code developed through years of research! Implements optimization algorithms with fitness functions, selection methods, crossover operations, and mutation mechanisms for solving complex problems.
A comprehensive MATLAB implementation of the basic ant colony algorithm for solving Traveling Salesman Problem (TSP), featuring detailed code comments and graphical result visualization to facilitate learning and understanding.
A path planning solution utilizing Particle Swarm Optimization algorithm with basic functionality, where obstacles are represented as discrete points in the environment.
Implementation of character recognition in MATLAB using neural network-based approach with code examples and algorithm explanations.
Implementation of Ant Colony Algorithm for Traveling Salesman Problem with path optimization using att48 dataset containing 48 cities, featuring parameter tuning and de-crossing techniques for enhanced solution quality.
To address large-scale Traveling Salesman Problem (TSP) challenges, we propose a Tower-like Master-Slave Model (TMSM) for parallel artificial immune systems and a Parallel Immune Memory Clonal Selection Algorithm (PIMCSA) based on TMSM architecture.
A comprehensive MATLAB implementation comparing Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), demonstrating their respective advantages and limitations through performance analysis and application scenarios
Implementation of 2D path planning on grid maps using ant colony optimization algorithm, featuring practical applications and detailed code implementation insights for enhanced routing efficiency
k-medoids Network Community Clustering with User Manual and Algorithm Principles
This implementation performs feature extraction using Gabor wavelet filters, then employs Support Vector Machine (SVM) classification for face detection. The code requires MATLAB 2010 or later versions for execution, utilizing MATLAB's image processi
MATLAB-based implementation of artificial immune genetic algorithm with detailed code comments, designed to assist in solving optimization problems through immune system-inspired evolutionary computation.
A simulation example modeling robotic arm motion joints using RBF neural networks. The implementation demonstrates joint trajectory learning and control through radial basis function networks with practical code structure explanations.
MATLAB implementation of fuzzy clustering analysis with graphical visualization of clustering results, featuring data preprocessing, algorithm parameter tuning, and result interpretation.
Binary Particle Swarm Optimization (PSO) algorithm implementation with main program: swarmpso.m. Contains modular subroutines for swarm initialization, fitness evaluation, and particle position updates in discrete binary space.
PSO (Particle Swarm Optimization) Algorithm Toolbox for solving complex optimization problems through swarm intelligence.