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  1. sites.pitt.edu

    Parunak, Savit, and Riolo, "Agent-Based Modeling vs. Equation-Based Modeling" Page 2 This paper explores the question in the problem domain of manufacturing supply networks, and giving examples of both ABM's and EBM's (Section 2). It discusses the relation between these two approaches at a high level (Section 3), and then
  2. sne-journal.org

    the modeling and simulation of cyber-physical systems. Since it is based on equations, this modeling language is applicable to a multitude of physical domains and especially suited for complex physical systems and their control. This paper provides a brief introduction on the kind of equation-based modelling promoted by Modelica and its underlying
  3. Simulating the KdV Equations with Equation-Based Modeling. To solve the KdV equation in COMSOL Multiphysics, users can add PDEs and ODEs into the software interface via mathematical expressions and coefficient matching. It's also possible to easily define dependent variables and identify coefficients via the General Form PDE interface.
  4. 2.2 Equation-Based Models Historically equation based models have been used to model the spread of in-fectious diseases. The most common type of equation based model used for in-fectious disease modelling is the compartmental model, which is made up of a set of di erential equations [13]. The population in a compartmental model is
  5. help.modelon.com

    Modelon Impact is based on the idea of modeling reuse and acausal modeling. Acausal modeling is also known as equation-based or physics-based modeling. The idea behind this is that you never have to write a piece of code more than once. This means that you define the behavior of the model via equations but leave out the order of the ...
  6. doc.comsol.com

    T his chapter describes the use of the interfaces for mathematics and equation-based modeling, found under the Mathematics branch when adding interfaces.With these interfaces, you can solve various types of PDEs using different formulations. You can also solve ODEs and other global equations as well as create events, create curvilinear coordinates, and use extra dimensions.
  7. help.modelon.com

    • Acausal nature of Modelica models makes it a very good candidate for automatic inversion of models • Modelica models are automatically rearranged based on boundary condition imposition during translation process in a tool • Impact's symbolic processing capabilities help the model inversion with very less user effort INVERSE MODELING
  8. sciencedirect.com

    Models composed of such equations, which treat time as evolving in discrete steps, are similar to the cellular automata or agent-based models, in which the rules of the biology are included in the mapping [1].There is no obstacle to including several interacting variables, or even values from multiple different time steps, within a difference equation.
  9. 3. Equation-Based Modeling vs. Agent-Based Modeling 3.1. The Spread of Epidemics as a Complex System The spread of an epidemic within a population is a purely dynamic phenomenon: the numbers of healthy and sick individuals evolve according to the time constraint, depending on the time during which this agent changes from an infected individual to a
  10. imath-asia.com

    • What about non-linear equations with multiple solutions? • Which solution do you get? • For simplicity, consider the equation (u-2)^2-p=0, where p is a constant • The solution you get will depend on the Initial Guess given by the PDE Physics Interface • If we let p=x*y and let our modeling region be the unit square, then at

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