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    Potential Scenario
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    2011-Gaff-Lenhart-Use of optimal control models to predict treatment time for managing tick-borne disease
    Tick-borne diseases have been on the rise recently, and correspondingly, there is an increased interest in implementing control measures to decrease the risk. Optimal control provides an ideal tool to identify the best method for reducing risk.
    Potential Scenario
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    1972-Suresh_Sethi-Optimal Control of the Vidale-Wolfe Advertising Model
    This paper considers an optimal-control problem for the dynamics of the Vidale-Wolfe advertising model, the optimal control being the rate of advertising expenditure to achieve a terminal market share within specified limits.
    Modeling Scenario
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    1-155-CruiseControl-ModelingScenario
    In this project we illustrate the design of a proportional-integral-derivative (PID) cruise control algorithm for an automobile. PID control is one of the most common techniques in control engineering.
    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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    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).
    Potential Scenario
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    2004-Ledzewicz-Schattler-Application of Control Theory in Modelling Cancer Chemotherapy
    In this paper we discuss how to incorporate more realistic medical aspects of chemotherapy which hitherto have been neglected in the models.
    Article or Presentation
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    2013-Brian_Winkel-An_Optimal_Control_Model_in_Insect_Colonies
    we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at the end of a season.
    Potential Scenario
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    2017-Sim-EtAl-Optimal control of a coupled tanks system with model-reality differences
    In this paper, an efficient computational approach is proposed to optimize and control a coupled tanks system.
    Potential Scenario
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    2009-James_May-Nonlinear vibration control of long flexible structures
    An automated, non-linear control scheme was developed to transfer energy from the fundamental vibration mode, where most vibration energy of the structures of interest resides, to higher order modes where vibration impedance was shown to be...
    Potential Scenario
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    1977-Michael_Mackey-Leon_Glass-Oscillation and Chaos in Physiological Control Systems
    First-order nonlinear differential-delay equations describing physiological control systems are studied. The equations display a broad diversity of dynamical behavior including limit cycle oscillation.
    Potential Scenario
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    2012-Bech-EtAl-Resources For Engineering Applications Of Math
    Illustrations of applied mathematics including statics, truss, heat equation, column analysis, coupled oscillators, feedback control, AC circuit, chemical reactions, kinetics.
    Potential Scenario
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    2017-Chávez-EtAl-Modeling and Analysis of Integrated Pest Control Strategies via Impulsive Differential Equations
    The paper is concerned with the development and numerical analysis of mathematical models used to describe complex biological systems in the framework of Integrated Pest Management (IPM).
    Potential Scenario
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    2006-Ousmane_Mousa_Tessa-Mathematical model for control of measles by vaccination
    In this article, we use a compartmental mathematical model of the dynamics of measles spread within a population with variable size to provide this framework.
    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.
    Modeling Scenario
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    6-005-InsectColonySurvivalOpt-ModelingScenario
    We present a system of nonlinear differential equations to model the control of energy flow into producing workers or reproducers in an insect colony, using a set of given parameters and a number of different energy functions.
    Potential Scenario
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    2008-Ratneesh_Suri-Optimal harvesting strategies for fisheries-differential equations approach
    We develop and investigate the harvesting model in both deterministic and stochastic settings. We first employ the Expected Net Present Value approach and determine optimal harvesting policy using various optimization techniques including optimal...
    Potential Scenario
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    2017-Jean-Roux-Mathematical Models in Air Quality Problems
    Presents many models with analysis in air quality control. Starts with chemical kinetics models and builds complexity to PDE models.
    Potential Scenario
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    2005-DieboldEtAl-Modeling Bond Yields In Finance And Macroeconomics
    From a macroeconomic perspective, the short-term interest rate is a policy instrument under the direct control of the central bank. From a finance perspective, long rates are risk-adjusted averages of expected future short rates.
    Potential Scenario
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    1994-S_S_Everingham-C_Peter_Rydell-Modeling the Demand for Cocaine
    This is a report prepared for the Office of National Drug Control Policy of the United States Army by the Rand Corporation. The report contains lots of data and builds a two compartment difference equation model.
    Potential Scenario
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    2014-Do-Lee-A Differential Equation Model for the Dynamics of Youth Gambling
    We examine the dynamics of gambling among young people aged 16–24 years, how prevalence rates of at-risk gambling and problem gambling change as adolescents enter young adulthood, and prevention and control strategies.