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    Potential Scenario
    169

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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.
    population dynamicsLogistic modelMalthus ModelPopulation Prediction Control
    Potential Scenario
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    35

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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.
    population dynamicsextinctionlogisticTibetan antelope
    Potential Scenario
    107

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    34

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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.
    diseasespreadcarriessymptomaticasymptomatic
    Potential Scenario
    172

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    55

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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.
    population dynamicsLotka-Volterragrowth ratemutualismLichen
    Potential Scenario
    157

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    46

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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).
    population growthlogistic growthDrug and Alcohol detoxificationcarrying capacityvital coefficients
    Potential Scenario
    175

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    76

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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.
    logisticIndiavital coefficientsAsiaCarrying Vapacitiyannual growth rate
    Potential Scenario
    128

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    41

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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.
    sustainabilityfishFishingmanagementharvestfisherstrategyoverfishing
    Potential Scenario
    172

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    35

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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.
    population dynamicslogistic equationlocation-dependent carrying capacities
    Potential Scenario
    189

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    72

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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.
    Optimal Control TheoryJacobianSolow-Swan modelMonetary policyoptimal economic growth
    Potential Scenario
    111

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    41

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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.
    fisheriesEuler's methodnonlinearlogistic harvestingcanabalismsalmon
    Modeling Scenario
    176

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    495

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    1-124-WorldPopulation-ModelingScenario
    We build models of world population using data to estimate growth rate.
    population dynamicshumangrowth ratevarying growth rate
    Modeling Scenario
    206

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    317

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    1-170-CensusModeling-ModelingScenario
    Students who have studied models for population are likely to be familiar with the exponential and the logistic population models. The goal here is to explore the role of modeling assumptions in choosing which model to use.
    logistic growthexponentialpopulationU.S. Census DataassumptionGoogle SheetsUnites StatesGuatemala
    Potential Scenario
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    46

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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.
    diseaselogisticHIVpiecewise constantIndia
    Potential Scenario
    149

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    35

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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.
    population modelReproductionspline approximationsBombus terrestrisneonicotinoidsbumble bee
    Potential Scenario
    121

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    38

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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.
    population dynamicsparameter estimationlimited growthgrowthlogisitic
    Potential Scenario
    168

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    49

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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...
    epidemiologypopulationpublic opinion
    Modeling Scenario
    320

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    124

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    1-039-StochasticPopModels-ModelingScenario
    We develop strategies for creating a population model using some simple probabilistic assumptions. These assumptions lead to a system of differential equations for the probability that a system is in state (or population size) n at time t.
    Probabilitypopulation dynamicsVarianceMeanstochasticdeterministic
    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.
    population dynamicspredator-preylogistic equationEndangered Catsdecreasing populationrabbitsfoxes
    Potential Scenario
    134

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    47

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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.
    combat modelguerrilla warfaregovernment
    Modeling Scenario
    161

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    1-134-LanguageDynamics-ModelingScenario
    Students will be introduced to a mathematical model for language dynamics. Specifically, the model describes the change in the fraction of a population speaking one language over another.
    languagecompartmentphase linesbifurcationswitching