Energy approach in modeling population dynamics
To understand the functioning mechanisms and problem solutions of the use of populations, information about their structure is of great importance. The study of regularities of animals population dynamics is needed to create a scientific basis of the rational use of pest destroying animals and pest...
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2013-10-01
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Online Access: | http://journals.uran.ua/tarp/article/view/18224 |
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doaj-8e2728f20e5a4ff18a5c64c3a4757a722020-11-25T02:20:20ZengPC Technology CenterTehnologìčnij Audit ta Rezervi Virobnictva2226-37802312-83722013-10-0154(13)202110.15587/2312-8372.2013.1822418224Energy approach in modeling population dynamicsИгорь Анатольевич Пилькевич0Zhytomyr National Agroecological University Blvd Stary, 7, Zhytomyr, Ukraine, 10008To understand the functioning mechanisms and problem solutions of the use of populations, information about their structure is of great importance. The study of regularities of animals population dynamics is needed to create a scientific basis of the rational use of pest destroying animals and pest control. Herewith, mathematical methods, in particular modeling, are used. Among the population dynamics models, the Verhulst’s logistic function (1838) is the most widespread in mathematical ecology. It is used to describe both the behavior of populations and their interaction, for example, in the Lotka-Volterra equations. Recent studies have shown the impossibility of using the logistic models in predicting the development dynamics of objects of different nature. The methodology for constructing mathematical models of population dynamics is proposed in the paper. It is fair for mathematical description of objects of different nature. Systematology is the theoretical basis for the construction of mathematical models.http://journals.uran.ua/tarp/article/view/18224logistic modelpopulation dynamicssystems theoryenergy approach |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Игорь Анатольевич Пилькевич |
spellingShingle |
Игорь Анатольевич Пилькевич Energy approach in modeling population dynamics Tehnologìčnij Audit ta Rezervi Virobnictva logistic model population dynamics systems theory energy approach |
author_facet |
Игорь Анатольевич Пилькевич |
author_sort |
Игорь Анатольевич Пилькевич |
title |
Energy approach in modeling population dynamics |
title_short |
Energy approach in modeling population dynamics |
title_full |
Energy approach in modeling population dynamics |
title_fullStr |
Energy approach in modeling population dynamics |
title_full_unstemmed |
Energy approach in modeling population dynamics |
title_sort |
energy approach in modeling population dynamics |
publisher |
PC Technology Center |
series |
Tehnologìčnij Audit ta Rezervi Virobnictva |
issn |
2226-3780 2312-8372 |
publishDate |
2013-10-01 |
description |
To understand the functioning mechanisms and problem solutions of the use of populations, information about their structure is of great importance. The study of regularities of animals population dynamics is needed to create a scientific basis of the rational use of pest destroying animals and pest control. Herewith, mathematical methods, in particular modeling, are used. Among the population dynamics models, the Verhulst’s logistic function (1838) is the most widespread in mathematical ecology. It is used to describe both the behavior of populations and their interaction, for example, in the Lotka-Volterra equations. Recent studies have shown the impossibility of using the logistic models in predicting the development dynamics of objects of different nature.
The methodology for constructing mathematical models of population dynamics is proposed in the paper. It is fair for mathematical description of objects of different nature. Systematology is the theoretical basis for the construction of mathematical models. |
topic |
logistic model population dynamics systems theory energy approach |
url |
http://journals.uran.ua/tarp/article/view/18224 |
work_keys_str_mv |
AT igorʹanatolʹevičpilʹkevič energyapproachinmodelingpopulationdynamics |
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1724872022941499392 |