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A review of clonal selection algorithm and its applications

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TLDR
The powerful characteristics and general review of CSA are summarized, CSA based hybrid algorithms are reviewed, and open research areas are discussed for further research.
Abstract
Recently, clonal selection theory in the immune system has received the attention of researchers and given them inspiration to create algorithms that evolve candidate solutions by means of selection, cloning, and mutation procedures. Moreover, diversity in the population is enabled by means of the receptor editing process. The Clonal Selection Algorithm (CSA) in its canonical form and its various versions are used to solve different types of problems and are reported to perform better compared with other heuristics (i.e., genetic algorithms, neural networks, etc.) in some cases, such as function optimization and pattern recognition. Although the studies related with CSA are increasingly popular, according to our best knowledge, there is no study summarizing the basic features of these algorithms, hybrid algorithms, and the application areas of these algorithms all in one paper. Therefore, this study aims to summarize the powerful characteristics and general review of CSA. In addition, CSA based hybrid algorithms are reviewed, and open research areas are discussed for further research.

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References
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Journal ArticleDOI

Learning and optimization using the clonal selection principle

TL;DR: This paper proposes a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response and derives two versions of the algorithm, derived primarily to perform machine learning and pattern recognition tasks.
Book

The clonal selection theory of acquired immunity

F. M. Burnet
TL;DR: The clonal selection theory of acquired immunity is studied as a theory of selection for immunity in the context of infectious disease.
Book

Artificial Immune Systems: A New Computational Intelligence Approach

TL;DR: The AIS in Context with Other Computational Intelligence Paradigms and Case Studies shows how the immune system in context with other biological systems and other paradigms has changed since the 1970s.
BookDOI

Artificial Immune Systems and Their Applications

TL;DR: This book provides an overview of artificial immune systems, explaining its applications in areas such as immunological memory, anomaly detection algorithms, and modeling the effects of prior infection on vaccine efficacy.
Journal ArticleDOI

Architecture for an Artificial Immune System

TL;DR: In this paper, ARTIS is applied to computer security in the form of a network intrusion detection system called LISYS, which is shown to be effective at detecting intrusions, while maintaining low false positive rates.
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