High Usability of Immune Genetic Algorithm Implementation
My custom-developed immune genetic algorithm demonstrates strong usability - simply modify parameter module names for different applications
Explore MATLAB source code curated for "免疫遗传算法" with clean implementations, documentation, and examples.
My custom-developed immune genetic algorithm demonstrates strong usability - simply modify parameter module names for different applications
This is an author-developed program written in MATLAB language, implementing an immune genetic algorithm for optimization problems. Includes algorithm design and code architecture descriptions.
A well-designed MATLAB program implementing immune genetic algorithm for optimization problems, with comprehensive code explanations and algorithm insights
MATLAB program for Immune Genetic Algorithm featuring six core modules: antigen recognition, initial antibody generation, fitness evaluation, memory cell differentiation, antibody promotion and suppression, and antibody reproduction (crossover and mutation)
A comprehensive guide featuring MATLAB code implementation for immune genetic algorithms, including fitness function design, parameter configuration, and optimization techniques.
Immune Genetic Algorithm for population optimization - MATLAB program implementation with comprehensive references for further study.
MATLAB implementation of immune genetic algorithm for TSP, with comparative analysis between immune algorithm and genetic algorithm, featuring code structure explanations and performance comparisons
The Immune Genetic Algorithm searches for global optimal solutions with verified high efficiency and fast convergence properties, implementing evolutionary mechanisms through code-level operations like antibody cloning and mutation.
Source code for immune genetic algorithm featuring comprehensive program annotations, genetic algorithm workflow explanation, and immune selection mechanisms. Includes practical implementation approaches and key function descriptions.
Advanced Immune Genetic Algorithm Implementation with Code-Oriented Descriptions