Negative Selection Algorithm Research and Applications in the Last Decade: A Review

The Negative selection Algorithm (NSA) is one of the important methods in field Immunological Computation (or Artificial Immune Systems). Over years, some progress was made which turns this algorithm into an efficient approach to solve problems different domain. This review takes account these signs during last decade and categorizes those based on characteristics performances. Our study shows that NSA's evolution can be labeled four ways highlighting most notable NSA variations their limitations application domains. We also present alternative approaches for comparison analysis. It evident performs better nonlinear representation than other methods, it outperform neural-based models computation time. summarize development highlight challenges research with similar models.