Time-dependent solution of the logistic model for population growth in random environment

1980 ◽  
Vol 17 (4) ◽  
pp. 1083-1086 ◽  
Author(s):  
Prajneshu
Keyword(s):  
Population Growth ◽  
Stationary Solution ◽  
Random Environment ◽  
Carrying Capacity ◽  
Logistic Model ◽  
Time Dependent ◽  
Kolmogorov Equation ◽  
Exact Time ◽  
Time Dependent Solution

The exact time-dependent solution as well as the stationary solution of the logistic model for population growth with varying carrying capacity is worked out in both the Stratonovich and Ito calculi by solving the forward Kolmogorov equation.

Time-dependent solution of the logistic model for population growth in random environment

1980 ◽  
Vol 17 (04) ◽  
pp. 1083-1086
Author(s):  
Prajneshu
Keyword(s):  
Population Growth ◽  
Stationary Solution ◽  
Random Environment ◽  
Carrying Capacity ◽  
Logistic Model ◽  
Time Dependent ◽  
Kolmogorov Equation ◽  
Exact Time ◽  
Time Dependent Solution

The exact time-dependent solution as well as the stationary solution of the logistic model for population growth with varying carrying capacity is worked out in both the Stratonovich and Ito calculi by solving the forward Kolmogorov equation.

scholarly journals Psi-Caputo Logistic Population Growth Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Muath Awadalla ◽  
Yves Yannick Yameni Noupoue ◽  
Kinda Abu Asbeh
Keyword(s):  
Population Growth ◽  
Fractional Derivative ◽  
Carrying Capacity ◽  
Chinese Population ◽  
Logistic Model ◽  
Logistic Equation ◽  
Logistic Growth ◽  
Growth Equation ◽  
Uniqueness Of The Solution ◽  
Better Than

This article studies modeling of a population growth by logistic equation when the population carrying capacity K tends to infinity. Results are obtained using fractional calculus theories. A fractional derivative known as psi-Caputo plays a substantial role in the study. We proved existence and uniqueness of the solution to the problem using the psi-Caputo fractional derivative. The Chinese population, whose carrying capacity, K, tends to infinity, is used as evidence to prove that the proposed approach is appropriate and performs better than the usual logistic growth equation for a population with a large carrying capacity. A psi-Caputo logistic model with the kernel function x + 1 performed the best as it minimized the error rate to 3.20% with a fractional order of derivative α  = 1.6455.

scholarly journals Population prediction of purwanegara village, Indonesia using modified logistic model with migration factor

2018 ◽  
Vol 7 (3) ◽  
pp. 1962
Author(s):  
Diandra Chika Fransisca ◽  
Padosroha Marbun
Keyword(s):  
Population Growth ◽  
Equilibrium Point ◽  
Growth Model ◽  
Carrying Capacity ◽  
Logistic Model ◽  
Central Java ◽  
Migration Factor ◽  
Central Java Province ◽  
Population Prediction ◽  
Birth Death

Population growth model is a widely been used model to do an estimation and forecasting towards the population of peoples, animals, bac-teria and even in economics growth. Many studies have been carried out on population growth model concerning the factors of birth, death and carrying capacity in order to predict the number of population at certain area. From these studies there is only one study involved the constant value factor of migration as an input in the logistic model. Therefore contradicting with the above modified logistic model, in this study logistic model is modified by adding a migration factor as a function of population. This function takes into account the migration and the interaction between peoples that is limited to the carrying capacity of the environment. This model can be solved qualitatively using the analysis of equilibrium point and quantitatively using the separable variables method. This modified logistic model with migration factor has been applied in the population prediction of Purwanegara village in Central Java Province, Indonesia. Throughout the results, the modified logistic model with migration factor as a function of population gives a better result for population prediction of Purwanegara village in Central Java Province, Indonesia compared with logistic model.  

Ideally conducting magnetostatic equilibria and associated time dependent, resistive flows

1971 ◽  
Vol 6 (1) ◽  
pp. 125-136 ◽  
Author(s):  
John C. Stevenson
Keyword(s):  
Magnetic Field ◽  
Energy Equation ◽  
Incompressible Flows ◽  
Neutral Point ◽  
Time Dependent ◽  
Two Dimensional ◽  
Exact Time ◽  
Field Lines ◽  
Time Dependent Solution ◽  
The Magnetic Field

Several types of two-dimensional solutions for the equations of magnetohydrodynamics are described. For all these solutions the magnetic field contains at least one hyperbolic neutral point. Two new magnetostatic equilibria are introduced for the ideally conducting case. The magnetic field associated with one of these is used to construct an exact time-dependent solution of the MilD equations where the fluid is necessarily at rest. In the case where the field lines are hyperbolae, it is demonstrated that retention of the energy equation (ordinarily decoupled for incompressible flows) implies that the flow beginning at rest, remains at trest

Population strategies and random environments

1975 ◽  
Vol 53 (2) ◽  
pp. 160-165 ◽  
Author(s):  
Hugh Barclay
Keyword(s):  
Population Growth ◽  
Stochastic Models ◽  
Carrying Capacity ◽  
Death Rate ◽  
Logistic Model ◽  
Birth Rate ◽  
Environmental Variation ◽  
Random Environments ◽  
Probability Of Extinction ◽  
Established Species

It is shown using several models that r and K selection may result from random environmental variation. Probabilities of extinction are derived for both colonizing and well-established species using stochastic models similar to the logistic model, and it is shown that the probability of extinction of a population can be reduced by increasing the birth rate or the carrying capacity or by decreasing the death rate or the effects of the environmental variation on population growth. It is probable that random environmental variation mainly facilitates r selection.

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