Explore MATLAB source code curated for "人工免疫算法" with clean implementations, documentation, and examples.
This is a series of artificial immune algorithm programs I obtained from foreign websites through a friend, containing numerous algorithm source codes implemented in MATLAB, which are highly beneficial for research in this field.
Implementation of Artificial Immune Algorithm and Neural Network for Bearing Pattern Recognition and MATLAB-based Fault Diagnosis with Code Examples
This algorithm implements an artificial immune system based on clonal selection principles. It consists of three components: the first part employs traditional genetic algorithms, while the second part utilizes the Clonal Selection Algorithm (CSA). Both methods are applied to extremum optimization for mathematical functions, enabling comparative analysis of their distinct characteristics through practical implementation.
MATLAB-based artificial immune algorithm implementation with applications in fault diagnosis systems, featuring immune-inspired optimization mechanisms and pattern recognition capabilities.
A comprehensive tutorial presentation on Artificial Immune Systems (AIS), covering artificial immune algorithms with practical implementation insights. Essential learning resource for those interested in bio-inspired computing approaches.
A comprehensive MATLAB program implementing artificial immune algorithm, featuring clear code structure with key functions for antibody initialization, affinity calculation, cloning operation, and mutation processes - highly valuable for beginners in optimization algorithms.
MATLAB-based program design comparison between Artificial Immune Algorithm and Genetic Algorithm implementations for Traveling Salesman Problem (TSP) research, featuring code analysis and performance evaluation.
A MATLAB implementation of artificial immune algorithm for simulation analysis of various engineering technical methods, featuring optimization capabilities through immune system principles simulation.
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 interaction simulations.
Artificial Immune Algorithm program implementation in MATLAB, featuring immune-inspired optimization techniques for problem-solving applications.