Source Code for Optimizing BP Neural Networks Using Genetic Algorithms
Reprinted source code focusing on fitness function implementation in genetic algorithm-optimized BP neural networks
Professional MATLAB source code with comprehensive documentation and examples
Reprinted source code focusing on fitness function implementation in genetic algorithm-optimized BP neural networks
Custom-developed code combining genetic algorithm with BP neural network for multi-objective optimization on neural network models! Includes detailed documentation with comprehensive results explanation! Implements BP-GA multi-objective optimization
MATLAB implementation of Radial Basis Function Neural Networks for prediction tasks, featuring algorithm explanation and key function descriptions
MATLAB-based BP Neural Network Implementation for Remote Sensing Image Classification with Code Optimization Techniques
MATLAB source code implementation of Particle Swarm Optimization (PSO) algorithm for finding optimal numerical solutions in solution space, featuring customizable parameter configuration and objective function handling.
Essential learning resource for Convolutional Restricted Boltzmann Machines in deep learning, facilitating understanding of methodological principles with code implementation insights.
MATLAB implementation of fuzzy clustering algorithm with comprehensive code structure, featuring key functions like fuzzy c-means (FCM) initialization, membership matrix calculation, and cluster centroid updates.
This program implements workpiece image preprocessing and edge extraction, combining improved genetic algorithms with Hausdorff distance for object recognition. It utilizes Canny edge detection as matching features, employs modified Hausdorff distanc
Implementation of standard Particle Swarm Optimization (PSO) algorithm for large-scale power system optimization with 40-node problem configuration
A program utilizing genetic algorithms for multivariate regression fitting with excellent performance and reliable results! Highly recommended implementation featuring chromosome encoding, fitness evaluation, and population evolution mechanisms.
GentleBoost - A popular machine learning algorithm variant that iteratively combines weak classifiers into a strong classifier, widely applied in computer vision and NLP with robust implementation characteristics.
High-quality adaptive genetic algorithm source code with significant reference value, featuring self-adjusting parameters and robust optimization capabilities
A genetic algorithm implementation designed to optimize kernel function parameters and related hyperparameters for Support Vector Machines (SVM), featuring selection, crossover, and mutation operations with fitness evaluation through model performanc
A genetic algorithm program implementation featuring selection, crossover, and mutation operations with fitness evaluation functions
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MATLAB implementation of RBF neural network for classification tasks, featuring parameter customization and adaptable code structure for various datasets
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Ready-to-run MATLAB implementation of the standard Particle Swarm Optimization algorithm with complete source code
Genetic Algorithm Toolbox featuring crossover, inheritance, and operators - excellent for optimization problems
Implementation of fundamental and improved Particle Swarm Optimization algorithms, including: Basic PSO for unconstrained optimization, Constriction Factor PSO, Linearly Decreasing Weight PSO, Adaptive Weight PSO, Random Weight PSO, Synchronous Learn