author_facet Figueroa, W
Prada, D
Vera, P
Gomez, J
Montes, E
Bautista, G
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Prada, D
Vera, P
Gomez, J
Montes, E
Bautista, G
author Figueroa, W
Prada, D
Vera, P
Gomez, J
Montes, E
Bautista, G
spellingShingle Figueroa, W
Prada, D
Vera, P
Gomez, J
Montes, E
Bautista, G
Journal of Physics: Conference Series
Analysis of population dynamics and chaos theory
General Physics and Astronomy
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spelling Figueroa, W Prada, D Vera, P Gomez, J Montes, E Bautista, G 1742-6588 1742-6596 IOP Publishing General Physics and Astronomy http://dx.doi.org/10.1088/1742-6596/1448/1/012001 <jats:title>Abstract</jats:title> <jats:p>Population growth is a topic of great interest to biologists, epidemiologists, ecologists, microbiologists and bioanalysts. Describing the dynamics of a population system through mathematical models is very useful in order to predict the behavior of the study population. Chaos theory supports studies of this type through the analysis of the logistic equation which allows observing this behavior under the variation of the constant k that represents the rate of increase in the number of times of the population values in a given time and the orbit diagram that summarizes the asymptotic behavior of all orbits in which we have values of k between zero and four. These models work with discrete time under measurement by iteration in observation and not continuously. The objective is to show the relationship of the logistic equation and the orbit diagram with the Feigenbaum constant in order to show the order that exists in the population dynamics.</jats:p> Analysis of population dynamics and chaos theory Journal of Physics: Conference Series
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title Analysis of population dynamics and chaos theory
title_unstemmed Analysis of population dynamics and chaos theory
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title_fullStr Analysis of population dynamics and chaos theory
title_full_unstemmed Analysis of population dynamics and chaos theory
title_short Analysis of population dynamics and chaos theory
title_sort analysis of population dynamics and chaos theory
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url http://dx.doi.org/10.1088/1742-6596/1448/1/012001
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description <jats:title>Abstract</jats:title> <jats:p>Population growth is a topic of great interest to biologists, epidemiologists, ecologists, microbiologists and bioanalysts. Describing the dynamics of a population system through mathematical models is very useful in order to predict the behavior of the study population. Chaos theory supports studies of this type through the analysis of the logistic equation which allows observing this behavior under the variation of the constant k that represents the rate of increase in the number of times of the population values in a given time and the orbit diagram that summarizes the asymptotic behavior of all orbits in which we have values of k between zero and four. These models work with discrete time under measurement by iteration in observation and not continuously. The objective is to show the relationship of the logistic equation and the orbit diagram with the Feigenbaum constant in order to show the order that exists in the population dynamics.</jats:p>
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author Figueroa, W, Prada, D, Vera, P, Gomez, J, Montes, E, Bautista, G
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description <jats:title>Abstract</jats:title> <jats:p>Population growth is a topic of great interest to biologists, epidemiologists, ecologists, microbiologists and bioanalysts. Describing the dynamics of a population system through mathematical models is very useful in order to predict the behavior of the study population. Chaos theory supports studies of this type through the analysis of the logistic equation which allows observing this behavior under the variation of the constant k that represents the rate of increase in the number of times of the population values in a given time and the orbit diagram that summarizes the asymptotic behavior of all orbits in which we have values of k between zero and four. These models work with discrete time under measurement by iteration in observation and not continuously. The objective is to show the relationship of the logistic equation and the orbit diagram with the Feigenbaum constant in order to show the order that exists in the population dynamics.</jats:p>
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spelling Figueroa, W Prada, D Vera, P Gomez, J Montes, E Bautista, G 1742-6588 1742-6596 IOP Publishing General Physics and Astronomy http://dx.doi.org/10.1088/1742-6596/1448/1/012001 <jats:title>Abstract</jats:title> <jats:p>Population growth is a topic of great interest to biologists, epidemiologists, ecologists, microbiologists and bioanalysts. Describing the dynamics of a population system through mathematical models is very useful in order to predict the behavior of the study population. Chaos theory supports studies of this type through the analysis of the logistic equation which allows observing this behavior under the variation of the constant k that represents the rate of increase in the number of times of the population values in a given time and the orbit diagram that summarizes the asymptotic behavior of all orbits in which we have values of k between zero and four. These models work with discrete time under measurement by iteration in observation and not continuously. The objective is to show the relationship of the logistic equation and the orbit diagram with the Feigenbaum constant in order to show the order that exists in the population dynamics.</jats:p> Analysis of population dynamics and chaos theory Journal of Physics: Conference Series
spellingShingle Figueroa, W, Prada, D, Vera, P, Gomez, J, Montes, E, Bautista, G, Journal of Physics: Conference Series, Analysis of population dynamics and chaos theory, General Physics and Astronomy
title Analysis of population dynamics and chaos theory
title_full Analysis of population dynamics and chaos theory
title_fullStr Analysis of population dynamics and chaos theory
title_full_unstemmed Analysis of population dynamics and chaos theory
title_short Analysis of population dynamics and chaos theory
title_sort analysis of population dynamics and chaos theory
title_unstemmed Analysis of population dynamics and chaos theory
topic General Physics and Astronomy
url http://dx.doi.org/10.1088/1742-6596/1448/1/012001