Mathematical modeling of population dynamics using differential equations

Population dynamics are used to give a mathematical explanation to changes in biological populations where they grow, compete, are limited by resources and affected by the environment.In this study, a framework for population analysis of temporal behavior is developed in the form of nonlinear governing equations of the form of differential equation.System variables that depend on population, assumptions used in the models, and equilibrium states and stability conditions are systematically formulated to describe long-term system behavior.Various population scenarios are represented by the model parameters and initial conditions.Numerical solution algorithm is used to approximate trajectories of populations for which analytical solutions are hard to come by.The suggested system measures changes in the size of the population, rate of growth, convergence to equilibrium and stability under varying parameter conditions.The examples show how differential equations can be used to model complex interactions in population dynamics and forecast changes in populations over time.

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Publication Details

Journal
Journal of Interdisciplinary Mathematics
Published
2026-10-27
DOI
https://doi.org/10.47974/jim-2828
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
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article

Mathematical modeling of population dynamics using differential equations

Ilhamdjan Karimdjanov, Lakhwinder Kaur, K. Prakash, H. Prasad et al.
5 links
Journal of Interdisciplinary Mathematics
Mathematical and Theoretical Epidemiology and Ecology Models
article

Mathematical modeling of population dynamics using differential equations

Ilhamdjan Karimdjanov, Lakhwinder Kaur, K. Prakash, H. Prasad, Tannmay Gupta, Soatmurod Boykobilov
article en

Abstract

Population dynamics are used to give a mathematical explanation to changes in biological populations where they grow, compete, are limited by resources and affected by the environment.In this study, a framework for population analysis of temporal behavior is developed in the form of nonlinear governing equations of the form of differential equation.System variables that depend on population, assumptions used in the models, and equilibrium states and stability conditions are systematically formulated to describe long-term system behavior.Various population scenarios are represented by the model parameters and initial conditions.Numerical solution algorithm is used to approximate trajectories of populations for which analytical solutions are hard to come by.The suggested system measures changes in the size of the population, rate of growth, convergence to equilibrium and stability under varying parameter conditions.The examples show how differential equations can be used to model complex interactions in population dynamics and forecast changes in populations over time.

Journal of Interdisciplinary MathematicsVol. 29(10)
Jain University (IN), Presidency University (IN), Termez University of Economics and Service (UZ), Rungta College of Engineering and Technology (IN), Tashkent State Medical University (UZ), Chitkara University (IN)
Openalex Percentile: Top 10%
Mathematical and Theoretical Epidemiology and Ecology Models
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Mathematical modeling of population dynamics using differential equations — Ilhamdjan Karimdjanov, Lakhwinder Kaur, et al. · Journal of Interdisciplinary Mathematics (2026) | TGRS Research Map | TGRS