Professional MATLAB source code with comprehensive documentation and examples
Swarm intelligence algorithms encompass ant colony optimization, particle swarm optimization, and artificial immune algorithms, with implementation approaches involving probabilistic path selection, velocity-position updates, and antibody-antigen int
A MATLAB genetic algorithm implementation for function optimization featuring comprehensive algorithmic steps with detailed code annotations covering selection, crossover, and mutation operations.
This excellent BP neural network program performs binary classification on two-class datasets, featuring gradient descent optimization and error backpropagation.
A must-have genetic algorithm toolkit with efficient optimization capabilities - download now before time runs out!
This is a MATLAB-implemented RBF neural network algorithm for handwritten digit recognition. The algorithm is operational when provided with corresponding handwritten digit images, featuring radial basis function layer implementation and pattern clas
MATLAB implementation for character and letter recognition using neural networks - a robust solution with practical applications. Download now for efficient pattern recognition capabilities.
Gene Classification in DNA Microarrays Using Recursive Feature Elimination with Support Vector Machines (RFE-SVM)
This resource provides comprehensive particle swarm optimization algorithms including CLPSO, CPSO, and FIPSO variants with detailed code implementations and optimization strategies
Implementation and analysis of SVM kernel function selection and construction techniques in MATLAB environment, including built-in functions and custom kernel development approaches for optimal model performance.
Ant Colony Optimization (ACO) is a novel evolutionary algorithm inspired by swarm intelligence. It mimics how ant colonies collaboratively seek food sources to solve complex discrete optimization problems. The algorithm has demonstrated exceptional p
Source code for implementing classification and function regression with Support Vector Machine (SVM), including practical examples. The provided code serves as a ready-to-use template, enabling users to replicate the implementation by following the
MATLAB implementation of artificial immune systems and genetic algorithms with comprehensive source code and optimization capabilities
MATLAB source code for training BP neural networks using Particle Swarm Optimization (PSO) algorithm, featuring complete implementation of hybrid optimization approach for neural network weight adjustment
MATLAB Implementation of HOG Feature Extraction and SVM Classification Methods for Person/Vehicle and Background Recognition
The Fuzzy C-Means (FCM) clustering method provides an efficient approach to image segmentation through pixel similarity-based clustering.
Practical implementation of Mean Shift for image segmentation with code-oriented explanations and algorithm insights that will benefit developers and researchers.
Implementation of Regression Prediction Models with Backpropagation Neural Networks
MATLAB SVM Toolbox - Practical Operations and Implementation for Support Vector Machines
MATLAB-based implementation of Backpropagation Neural Network with source code, providing practical guidance for neural network simulation in MATLAB environment, including key algorithm explanations and function descriptions.
Developing an improved differential evolution algorithm for optimizing neural network architectures and parameters