Genetic Algorithms + Data Structures = Evolution Programs

2000 ◽  
Vol 95 (449) ◽  
pp. 347 ◽  
Author(s):  
D. M. Rocke ◽  
Z. Michalewicz
Keyword(s):  
Genetic Algorithms ◽  
Data Structures ◽  
Evolution Programs

scholarly journals Optimization methodology of dynamic data structures based on genetic algorithms for multimedia embedded systems

2009 ◽  
Vol 82 (4) ◽  
pp. 590-602 ◽  
Author(s):  
Christos Baloukas ◽  
Jose L. Risco-Martin ◽  
David Atienza ◽  
Christophe Poucet ◽  
Lazaros Papadopoulos ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Data Structures ◽  
Dynamic Data Structures ◽  
Dynamic Data ◽  
Optimization Methodology

Recent Advances in Artificial Immune Systems

2017 ◽  
pp. 92-114 ◽  
Author(s):  
Florin Popentiu Vladicescu ◽  
Grigore Albeanu
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Data Structures ◽  
Clonal Selection ◽  
Artificial Immune Systems ◽  
Computing Methods ◽  
Artificial Immune ◽  
Immune Systems ◽  
Methods And Techniques ◽  
Soft Computing Methods

The designers of Artificial Immune Systems (AIS) had been inspired from the properties of natural immune systems: self-organization, adaptation and diversity, learning by continual exposure, knowledge extraction and generalization, clonal selection, networking and meta-dynamics, knowledge of self and non-self, etc. The aim of this chapter, along its sections, is to describe the principles of artificial immune systems, the most representational data structures (for the representation of antibodies and antigens), suitable metrics (which quantifies the interactions between components of the AIS) and their properties, AIS specific algorithms and their characteristics, some hybrid computational schemes (based on various soft computing methods and techniques like artificial neural networks, fuzzy and intuitionistic-fuzzy systems, evolutionary computation, and genetic algorithms), both standard and extended AIS models/architectures, and AIS applications, in the end.

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