Artificial Neural Network Model Builder
This MATLAB program provides a flexible framework for constructing artificial neural network models, allowing customizable layer configurations and neuron counts per layer.
MATLAB Function for Feature Selection Using Particle Swarm Optimization (PSO)
This MATLAB function implements Particle Swarm Optimization (PSO) for feature selection, offering customizable optimization direction, population size, iteration count, and other parameters with detailed algorithm implementation insights.
Particle Swarm Optimization and Enhanced PSO Algorithms
Classical implementation of Particle Swarm Optimization algorithms with improvements, featuring code explanations and practical examples for quick beginner mastery.
Nonlinear Integer Programming Problems with Genetic Algorithm Implementation
MATLAB Implementation for Nonlinear Integer Programming Using Genetic Algorithms - Exploring Heuristic Optimization Techniques with Code Examples
MATLAB Implementation of Wavelet Neural Networks
A wavelet neural network program derived from analog circuit fault diagnosis applications, provided for learning and reference purposes with detailed code implementation insights
Fundamental Theoretical Applications and Core Algorithms of Artificial Immune Systems
Simulation and Implementation of Basic Theories and Core Algorithms in Artificial Immune Systems
Support Vector Machine Toolbox
A Support Vector Machine Toolbox featuring MATLAB demonstration programs and essential functions including kernel computation functions, SVM training algorithms, and cross-validation functions for parameter selection. This toolbox provides efficient
Differential Evolution-Based Particle Swarm Optimization Algorithm
Differential Evolution-Based Particle Swarm Optimization (Global Best Particle Swarm Optimization) Algorithm
Genetic Algorithm MATLAB Toolbox Components
This code package contains partial implementations from the Genetic Algorithm MATLAB Toolbox, designed to work complementarily with GAmat1.rar and GAmat2.rar archives for comprehensive GA development.
MATLAB Genetic Algorithm for Single-Objective Optimization of Binary Function Maximization
MATLAB implementation of genetic algorithm for solving single-objective optimization problems to find maximum values of binary functions, featuring population initialization, fitness evaluation, selection, crossover, and mutation operations.
Implementation of Brushless DC Motor Control Using Compound Compensation Fuzzy Neural Network and PID
Implementation of compound control combining compensation fuzzy neural network and PID for brushless DC motors, achieving superior control performance through adaptive learning and stability optimization
Particle Swarm Optimization with Grid Method for Mobile Robot Shortest Path Planning
Implementing PSO-based Grid Approach for Optimal Path Planning in Mobile Robotics with Code Integration
Enhanced Genetic Optimization Algorithm for Addressing Local Minima Issues in BP Neural Networks
MATLAB-formatted source code implementing an improved genetic optimization algorithm to solve local minima problems in BP neural networks, featuring enhanced population initialization, adaptive crossover/mutation operations, and fitness-based selecti
Particle Swarm Clustering Algorithm Example with Code Implementation
Particle Swarm Clustering Algorithm Example and Detailed Analysis with Implementation Approaches
Solving Reactive Power Optimization Problem Using Genetic Algorithm
MATLAB source code implementing genetic algorithm for reactive power optimization in power systems
Genetic Algorithm for Multi-Objective Optimization Problems
This implementation utilizes genetic algorithms to solve multi-objective optimization problems, featuring efficient code structure and practical solution approaches that provide valuable insights for researchers and developers.
Various Decision Tree Classification Code Implementations
Comprehensive collection of decision tree classification algorithms including ID3, C4.5 implementations with runnable GUI interface and practical demonstrations
FCM Kernel Clustering Algorithm and Performance Analysis
Comprehensive analysis of FCM (Fuzzy C-Means) kernel clustering algorithm with visualization images, fuzzy C-means clustering diagrams, and interactive GUI interface implementation.
AdaBoost: The Classic Classification Algorithm with Code Implementation
AdaBoost: A fundamental classification algorithm accompanied by research papers and detailed program documentation, including code implementation guidelines
Self-Organizing Map (SOM) Networks in Neural Networks
Implementing data classification using Self-Organizing Map (SOM) networks from neural network architectures, with code implementation insights for competitive learning algorithms