Simulation Programs from Regular Practice on Artificial Immune Systems

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Resource Overview

This collection contains functional simulation programs developed during research on artificial immune systems, which resulted in a published paper. These implementations provide practical algorithms and modeling approaches particularly useful for graduate students (Masters/PhD candidates) encountering immune-inspired computing in their research.

Detailed Documentation

During my regular practice sessions, I developed simulation programs to study artificial immune systems, resulting in a published research paper. These simulations implement key artificial immune algorithms including clonal selection, negative selection, and immune network models, providing practical examples of population initialization, affinity calculation, and memory cell maintenance mechanisms. The code demonstrates parameter configuration for antigen-antibody interactions and includes visualization components for tracking algorithm convergence. These implementations are particularly valuable for graduate students (Masters/PhD candidates) who may encounter immune-inspired computing paradigms in their research, offering executable examples with documented parameter tuning approaches and performance evaluation metrics.

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