Support Vector Machine (SVM) Prediction Implementation
A well-structured MATLAB implementation for Support Vector Machine (SVM) prediction, featuring complete workflow from data loading to model evaluation
Decision Tree Implementation in MATLAB
MATLAB source code for decision tree algorithm implementation, providing a reference for machine learning applications with code structure explanations
Ant Colony Optimization: A Novel Metaheuristic Method for Combinatorial Optimization Problems with Code Implementation Insights
Ant Colony Optimization (ACO) is an innovative metaheuristic approach for solving combinatorial optimization problems, characterized by positive feedback mechanisms, distributed computation, and constructive greedy heuristic search properties. By est
PID Tuning Using Genetic Algorithm
Genetic Algorithm PID Tuning Problem: Known system parameters K=1 and T=2, using GA to optimize PID parameters. Encoding can be binary or real-valued with flexible bit length. Population size (M), crossover rate (Pc), and mutation rate (Pm) are user-
EEG Classification Using Fuzzy C-Means with Support Vector Machine Comparison
This project implements EEG classification with fuzzy C-means clustering and compares results against support vector machines using three distinct parameter optimization techniques.
Fuzzy Neural Networks for Function Approximation and Classification
Fuzzy neural network approximation and classification, fuzzy rule extraction, fast-growing and pruning network algorithms
Multi-Objective Genetic Algorithm (MOGA) Implementation
A versatile MOGA-based multi-objective genetic algorithm package with customizable parameters and modular architecture for diverse optimization applications.
Real-Coded Genetic Algorithm for Function Maximization
Real-Coded Genetic Algorithm for finding function maximum values - a highly practical implementation with detailed code-oriented explanations
Solving TSP Using Genetic Algorithm in MATLAB
Classic MATLAB implementation of genetic algorithm for Traveling Salesman Problem (TSP) with detailed code explanations
MATLAB Implementation of Backpropagation Neural Network Algorithm
Backpropagation Neural Network Algorithm for Pattern Recognition of Equipment Fault Types - Transformer Fault Identification Case Study with Simulation Data
LIBSVM Support Vector Machine
LIBSVM Support Vector Machine for classification identification. This program has been successfully applied in iris recognition research. It is a C program embedded in MATLAB with implementation details for algorithm integration.
Enhanced Level Set Segmentation Method with Integrated Spatial Fuzzy Clustering
An improved level set segmentation approach incorporating spatial fuzzy clustering, demonstrating superior segmentation performance with robust algorithm implementation
DBSCAN Clustering Implementation
This file contains a DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering code that helps you perform density-based data clustering. The implementation requires three input parameters: your dataset (feature matrix), the min
MATLAB Algorithm for Support Vector Data Description
MATLAB implementation of Support Vector Data Description (SVDD) algorithm for one-class classification, available for download with comprehensive code documentation and examples.
Neural Network Classification in MATLAB
Implementing neural network classification functionality in MATLAB by inputting training and test samples for model training and subsequent classification. This simple neural network algorithm is ideal for beginners, featuring clear implementation st
Neural Network Prediction Interface
A MATLAB-based neural network prediction interface with customizable data input and model configuration capabilities, providing users with an intuitive tool for implementing and testing neural network prediction algorithms.
MATLAB Implementation of AdaBoost Algorithm with Code Explanations
A practical MATLAB program implementing the AdaBoost algorithm, featuring fundamental code structures and implementation approaches for machine learning applications
Cross-Validation Subfunction for Parameters c and g in libsvm
Implementation and methodology for cross-validation of libsvm parameters c and g with code integration approaches
PSO Algorithm Optimization for PID Parameter Tuning
Implementation of PID parameter optimization using Particle Swarm Optimization (PSO) algorithm - This method has been published in a research paper demonstrating excellent control performance and convergence characteristics.
Wavelet Neural Network for Classification and Recognition
Wavelet Neural Network for classification and recognition tasks with customizable learning rate factor, network momentum factor, multi-resolution levels, and translation parameters. This example features 5 input nodes and 5 output nodes, capable of r