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Cosmological Parameter Estimation with Genetic Algorithms
Universe, 2023 Genetic algorithms are a powerful tool in optimization for single and multimodal functions. This paper provides an overview of their fundamentals with some analytical examples.
Ricardo Medel-Esquivel +4 more
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A new method for decoding an encrypted text by genetic algorithms and its comparison with tabu search and simulated annealing [PDF]
Management Science Letters, 2014 Genetic Algorithm is an algorithm based on population and many optimization problems are solved with this method, successfully. With increasing demand for computer attacks, security, efficient and reliable Internet has increased.
Mahdi Sadeghzadeh, Mahsa Taherbaghal
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An Automatic Document Classifier System Based on Genetic Algorithm and Taxonomy
IEEE Access, 2018 The use of the Web has increased the creation of digital information in an accelerated way and about multiple subjects. Text classification is widely used to filter emails, classify Web pages, and organize results retrieved by Web browsers. In this paper,
Alan Diaz-Manriquez +4 more
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Genetic algorithm and application
ScienceOpen Research, 2023 Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. They are considered as a search-based technique based on the principles of Genetics and Natural Selection used in computing to find an exact or approximate solution for ...
Khuong Le, Tianyu Wei, Justin Tagalogon
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Genetic Operators Applied to Symmetric Cryptography
International Journal of Interactive Multimedia and Artificial Intelligence, 2019 In this article, a symmetric-key cryptographic algorithm for text is proposed, which applies Genetic Algorithms philosophy, entropy and modular arithmetic.
Jefferson Rodríguez +2 more
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Parameter Selection in Genetic Algorithms [PDF]
Journal of Systemics, Cybernetics and Informatics, 2004 In this study, we provide a new taxonomy of parameters of genetic algorithms (GA), structural and numerical parameters, and analyze the effect of numerical parameters on the performance of GA based simulation optimization applications with experimental ...
Onur BOYABATLI, Ihsan SABUNCUOGLU
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Variations of Genetic Algorithms
CoRR, 2019 The goal of this project is to develop the Genetic Algorithms (GA) for solving the Schaffer F6 function in fewer than 4000 function evaluations on a total of 30 runs. Four types of Genetic Algorithms (GA) are presented - Generational GA (GGA), Steady-State (mu+1)-GA (SSGA), Steady-Generational (mu,mu)-GA (SGGA), and (mu+mu)-GA.
Alison Jenkins +3 more
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Multidimensional crossover in genetic algorithms
Journal of Numerical Analysis and Approximation Theory, 1999 Not available.
Márton-Ernö Balázs
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The Use of Genetic Algorithms for Searching Parameter Space in Gaussian Process Modeling
Journal of Telecommunications and Information Technology, 2015 The aim of the paper is to present the possibilities of modeling the experimental data by Gaussian processes. Genetic algorithms are used for finding the Gaussian process parameters.
Agnieszka Krok
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On the practical genetic algorithms [PDF]
Proceedings of the 7th annual conference on Genetic and evolutionary computation, 2005 This paper offers practical design-guidelines for developing efficient genetic algorithms (GAs) to successfully solve real-world problems. As an important design component, a practical population-sizing model is presented and verified.
Chang Wook Ahn +2 more
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