Professional MATLAB source code with comprehensive documentation and examples
NSGA-II is one of the most popular multi-objective genetic algorithms that reduces the complexity of non-dominated sorting genetic algorithms. It features fast execution speed, excellent solution set convergence, and serves as a benchmark for evaluat
A MATLAB implementation of RBF neural network specifically designed for stock market forecasting, featuring error analysis graphs and prediction visualization capabilities with customizable parameters and data processing functions.
Comprehensive directory of genetic algorithms with multiple practical examples, featuring code implementation details and algorithm explanations to accelerate learning for beginners
RBF neural network prediction program with comprehensive implementations for modeling, simulation, and experimental applications, featuring core algorithm explanations and key function descriptions
Implementation of grayscale image segmentation through integration of Pulse-Coupled Neural Network (PCNN) and clustering methods with code-level implementation insights
Support Vector Machine (SVM) is widely used in fault diagnosis due to its effectiveness in addressing nonlinear problems and handling small sample datasets.
GA-based parameter identification methodology for AutoRegressive with eXogenous input (ARX) models with evolutionary optimization implementation
Implementation of Adaboost algorithm combining weak classifiers into strong classifiers with visualization and analysis of sample size impact on performance
Implementation of Simulated Annealing Algorithm for Traveling Salesman Problem (TSP) Optimization
This program provides a comparative analysis of three evolutionary algorithms - Genetic Algorithm (GA), Quantum Genetic Algorithm (QGA), and a Novel Genetic Algorithm - using mathematical function optimization as test cases. The implementation demons
Implementation and analysis of RBF neural network prediction model using MATLAB source code, featuring detailed algorithm explanations and key function descriptions
This implementation provides four distinct SVM toolboxes for classification and regression algorithms: 1) LS_SVMlab toolbox with Classification_LS_SVMlab.m for multi-class classification and Regression_LS_SVMlab.m for function fitting using Least Squ
Practical Implementation and Programming Techniques of Self-Organizing Feature Maps in Neural Networks
Basic Genetic Algorithm Implementation for Solving Function Extremum Problems
Deep learning code resources for learners to study and implement neural network architectures, including practical examples with TensorFlow/PyTorch frameworks and algorithm explanations
Bayesian Machine Learning for mutual information calculation, entropy and joint entropy computation. Enhanced version applicable to stochastic inversion with improved uncertainty quantification.
Implementation code for "Constrained Spectral Clustering through Gaussian Process" by Lu Zhengdong from CVPR 2008, featuring directly executable algorithm with two demonstration examples
An annealing algorithm suitable for single-parameter optimization problems with practical implementation guidance
A comprehensive classic program integrating genetic algorithms and neural networks, featuring optimized initialization, crossover/mutation operations, backpropagation training, and multi-domain applications.
This program provides the source code implementation of an immune algorithm incorporating information entropy to solve the Traveling Salesman Problem (TSP). The code demonstrates how to integrate entropy measurements with immune system-inspired optim