Professional MATLAB source code with comprehensive documentation and examples
MATLAB-based implementation of Support Vector Machines (SVM) handling both linearly separable and non-separable cases, including nonlinear SVM with common kernel functions for enhanced classification and prediction analysis.
Particle Swarm Optimization Toolbox - Tested and proven highly effective, featuring intuitive implementation with swarm intelligence algorithms and parameter optimization capabilities for computational research support.
This program is designed for neural network beginners and comes with pre-loaded experimental data. It can be executed directly in MATLAB environment. Users can input new data sets and modify parameters for customization.
The backpropagation neural network algorithm represents one of the most advanced optimization solutions. This paper examines the widely-used feedforward neural networks and discusses key algorithmic improvements. While the error backpropagation (BP)
Cloud Multi-Objective Particle Swarm Optimization Algorithm implemented in MATLAB environment, with comprehensive code examples and detailed explanations for learners and researchers.
This program provides a MATLAB implementation using genetic algorithms to solve basic Vehicle Routing Problems. The distance matrix between supply points and genetic algorithm parameters are defined in VRP.M. The fitness function is calculated based
Solving VRP with Genetic Algorithm: Implementation and Code Approaches
Pattern Recognition MATLAB Toolbox containing approximately 130 pattern recognition programs and algorithms, including implementations for image recognition, speech recognition, and object detection.
Simulation of PSO Algorithm Implementation for Wind Energy MPPT System Optimization
Implemented MATLAB m-file code for Traveling Salesman Problem using genetic algorithm - thoroughly tested and fully functional
A simple neural network-based letter recognition program with clear implementation details and beginner-friendly code structure, featuring multi-layer perceptron architecture and backpropagation training.
A MATLAB-based image registration program utilizing mutual information metric and Particle Swarm Optimization algorithm for enhanced alignment accuracy and performance.
This article provides an in-depth explanation of the principles and source code implementations for function optimization (supporting both constrained and unconstrained problems) and combinatorial optimization algorithms. The presented algorithms dem
Utilizing the Bat Algorithm (BA) to optimize Extreme Learning Machine (ELM) input weights and biases significantly improves diagnostic accuracy. This implementation involves iterative parameter tuning through BA's echolocation-inspired search mechani
My custom-developed immune genetic algorithm demonstrates strong usability - simply modify parameter module names for different applications
This MATLAB implementation of the MOPSO algorithm provides a practical tool for solving multi-objective optimization problems. The code demonstrates particle swarm dynamics with Pareto-based selection mechanisms for engineering applications.
Three MATLAB implementations of Radial Basis Function (RBF) neural networks featuring distinct training methodologies: cluster-based RBF, gradient descent-based RBF, and Orthogonal Least Squares (OLS)-based RBF networks with detailed algorithmic desc
A random forest, as the name suggests, constructs a forest using random methods, comprising numerous decision trees where each tree operates independently without correlation. After the forest is built, when a new input sample arrives, each decision
By integrating multi-agent learning, coordination strategies, and particle swarm optimization, we propose a novel distribution network reconfiguration method based on multi-agent particle swarm optimization. This approach leverages the topological st
Microgrid multi-objective dispatch optimization employing an enhanced multi-objective particle swarm algorithm with three objective functions including economic efficiency