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    Potential Scenario
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    2014-XM-Huang-Ordinary Differential Equation Model and its Application in the Prediction Control of Population
    In this paper, we study two kinds of ordinary differential equation models, i.e., Malthus model and Logistic model, and discuss their applications in the prediction control of population.
    Potential Scenario
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    2007-Hui_Luo-Population Modeling by Differential Equations
    A general model for the population of Tibetan antelope is constructed. The present model shows that the given data is reasonably logistic.
    Potential Scenario
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    2010-Del-Ciello-EtAl-Modeling Disease
    We model the transmission of a disease through a population. Such modeling is very important to the study of epidemiology and the practice of medicine.
    Potential Scenario
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    2006-Graves-Peckham-Pastor-2D differential equations model for mutualism
    We develop from basic principles a two-species differential equations model which exhibits mutualistic population interactions.
    Potential Scenario
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    2012-Augustus-Wali-Mathematical Modeling of Uganda Population Growth
    The purpose of this paper focuses on the application of logistic equation to model the population growth of Uganda using data from 1980 to 2010 (inclusive).
    Potential Scenario
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    2017-Rosario-Antony-Mathematical Model for Future Population Scenario In India And China – An Econometric Approach
    A mathematical model including dynamical systems, statistical models and differential equations involves variety abstract structures. Population growth is one of the main issues in India and China which are located in Asia.
    Potential Scenario
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    2000-Idels-Wang-Harvesting Fisheries Management Strategies With Modified Effort Function
    This study concludes that a control parameter beta (the magnitude of the effect of the fish population size on the fishing effort function E), changes not only the rate at which the population goes to equilibrium, but also the equilibrium values.
    Potential Scenario
    213

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    2012-Michael_Kerckhove-From Population Dynamics to Partial Differential Equations
    This article illustrates PDE models for location-dependent carrying capacities, migrations, and the dispersion of a population.
    Potential Scenario
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    2017-Xiang_Liu-Mathematical Studies of Optimal Economic Growth Model with Monetary
    In this paper, efforts will be made to study an extended Neoclassic economic growth model derived from Solow-Swan Model and Ramsey-Cass-Koopsman Model.
    Potential Scenario
    145

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    2010-Keesom-EtAl-Fishing for Answers Investigating Sustainable Harvesting Ra
    The purpose of this report is to determine and propose a model by which an optimal harvesting frequency can be determined to maintain a steady population of Alaskan salmon.
    Potential Scenario
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    2016-Banks-EtAl-Modeling Bumble Bee Population Dynamics with Delay Differential Equations
    To provide a tool for projecting and testing sensitivity of growth of populations under contrasting and combined pressures, we propose a delay differential equation model that describes multi-colony bumble bee population dynamics.
    Potential Scenario
    216

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    60

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    2014-Bozkurt-Peker-Mathematical modelling of HIV epidemic and stability analysis
    A nonlinear mathematical model of differential equations with piecewise constant arguments is proposed. This model is analyzed by using the theory of both differential and difference equations to show the spread of HIV in a homogeneous population.
    Potential Scenario
    153

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    59

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    1999-Meyer-Ausubel-Carrying Capacity-A Model with Logistically Varying Limits
    This paper extends the logistic equation to simple growth model with a logistically increasing carrying capacity. This is applied to human population situations in several countries with fits to data.
    Potential Scenario
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    74

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    2018-Arden_Baxter-Modeling Public Opinion
    In this paper, we adapt the epidemiological models to model the dynamics of public opinion. Public opinion is any view prevalent among the general public. Our model considers any topic or issue in which the public has two decisive and opposing...
    Potential Scenario
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    2010-Shaza_Hussein-Predator-Prey Modeling
    The objective of this project was to create five projections of animal populations based on a simple predator-prey model and explore the trends visible.
    Potential Scenario
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    1988-Michael Intriligator-Dagobert Brito-A Predator-Prey Model of Guerrilla Warfare
    The authors present a three variable: numbers of guerrillas, numbers of regular (government) soldiers, and size of population controlled by the guerrillas, at time t), nonlinear system of three differential equations.
    Potential Scenario
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    2015-Joshi-EtAl-Optimal control of an SIR model with changing behavior through an education campaign
    We study stability analysis and use optimal control theory on the system of differential equations to achieve the goal of minimizing the infected population (while minimizing the cost).
    Article or Presentation
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    2011-Brian_Winkel-Parameter_Estimates_in_Differential_Equation_Models_for_Population_Growth
    We estimate the parameters present in several differential equation models of population growth, specifically single species exponential and logistic growth, and multiple species competition and predation models.
    Potential Scenario
    195

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    2008-Huet-Deffuant-Differential Equation Models Derived from an Individual-Based Model Can Help to Understand Emergent Effects
    We study a model of primacy effect on individual's attitude. Typically, when receiving a strong negative feature first, the individual keeps a negative attitude whatever the number of moderate positive features it receives afterwards.
    Potential Scenario
    238

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    2011-Radouane_Yafia-A Study of Differential Equations Modeling Malignant Tumor Cells in Competition with Immune System
    In this paper, we present a competition model of malignant tumor growth that includes the immune system response. The model considers two populations: immune system (effector cells) and population of tumor (tumor cells).