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Genetic Algorithms
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The article was published on 2002-01-01 and is currently open access. It has received 17039 citations till now.read more
Citations
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Journal ArticleDOI
COVNET: a cooperative coevolutionary model for evolving artificial neural networks
TL;DR: COVNET places as few restrictions as possible over the network structure, allowing the model to reach a wide variety of architectures during the evolution and to be easily extensible to other kind of neural networks.
Journal ArticleDOI
Genetic algorithms with memory-and elitism-based immigrants in dynamic environments
TL;DR: Experimental results show that the memory-based and elitism-based immigrants schemes efficiently improve the performance of genetic algorithms in dynamic environments.
Journal ArticleDOI
Chaotic gravitational constants for the gravitational search algorithm
TL;DR: Ten chaotic maps are embedded into the gravitational constant of the recently proposed population-based meta-heuristic algorithm called Gravitational Search Algorithm (GSA) and it is demonstrated that sinusoidal map is the best map for improving the performance of GSA significantly.
Journal ArticleDOI
Credit scoring, statistical techniques and evaluation criteria: a review of the literature: credit scoring, techniques & evaluation criteria: a literature review
Hussein A. Abdou,John Pointon +1 more
Book ChapterDOI
Evolutionary Optimization Algorithms
Luigi Fortuna,Gianguido Rizzotto,Mario Lavorgna,Giuseppe Nunnari,M. Gabriella Xibilia,Riccardo Caponetto +5 more
TL;DR: This chapter will describe evolutionary algorithms that seem to respond to the characteristics required by soft computing, both with regard to versatility and to the efficiency and goodness of the results obtained.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
Genetic Algorithms + Data Structures = Evolution Programs
TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Journal ArticleDOI
An Introduction to Genetic Algorithms.
TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Book
Handbook of Genetic Algorithms
TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
Journal ArticleDOI
An Introduction to Population Genetics Theory
James F. Crow,Motoo Kimura +1 more
TL;DR: An introduction to population genetics theory, An introduction to Population Genetics Theory, Population Genetics theory, Population genetics theory as discussed by the authors, Population genetics, population genetics, and population genetics theories, Population Genetic Theory