MATLAB Implementation of Artificial Immune Algorithm with Source Code
Debugged and optimized artificial immune algorithm source code in MATLAB, featuring effective performance with detailed implementation insights and function explanations.
Artificial Immune Algorithm Based on Clonal Selection Principle
This algorithm implements an artificial immune system based on clonal selection principles. The Clonal Selection Algorithm (CSA) can optimize various functions to find extremum values while comparing their distinctive characteristics through evolutionary operations.
MATLAB Implementation of Artificial Immune Algorithm
This MATLAB implementation of the artificial immune algorithm provides a fully executable framework with detailed code structure and algorithmic components for immediate research and experimentation.
Artificial Immune Algorithm
Artificial Immune Algorithm for Single-Objective and Multi-Objective Optimization Problems
MATLAB Implementation of Artificial Immune Algorithm with Code Descriptions
Artificial Immune Algorithm implementation using information entropy for antibody diversity measurement, with affinity maturation achieved through clone selection and hypermutation mechanisms
MATLAB-Based Artificial Immune Algorithm for Optimization
A MATLAB implementation of an artificial immune algorithm utilizing immune network modeling for optimizing function f(x1, x2) - featuring antibody-antigen interaction simulation and adaptive search mechanisms
Artificial Immune Algorithm Source Code with Implementation
This artificial immune algorithm source code implements a complete optimization process including: 1. Parameter initialization 2. Random population generation using pop=initpop(popsize, chromlength) 3. Fault type encoding with code(1,:) for normal, code(2,:) for 50%, code(3,:) for 150%, and Unnoralcode for measured 188% fault data 4. M-iteration loop featuring: objective function calculation using Euclidean distance [objvalue]=calobjvalue(pop,i), fitness evaluation fitvalue=calfitvalue(objvalue), selection operation newpop=selection(pop,fitvalue), crossover newpop=crossover(newpop,pc,k), and mutation newpop=mutation(newpop,pm)
MATLAB-Based Artificial Immune Algorithm Implementation
An open-source MATLAB implementation of artificial immune algorithm featuring comprehensive code structure, detailed algorithm explanations, and modular function design for easy customization and collaborative development.
Artificial Immune Algorithm
MATLAB implementation of the Artificial Immune Algorithm with ready-to-execute code