Modeling & Simulation

Modeling Terminology


Below is a list of a few common words that may have special meaning when applied to models. [1]

  • Accuracy: The closeness of a measured or modeled/computed value to its “true” value. The “true” value is the value it would have if we had perfect information. We will talk later about various ways to measure accuracy.
  • Algorithm: A set of rules for solving some problem. On a computer, an algorithm is a set of rules in computer code that solve a problem.
  • Calibration: The process of adjusting model parameters within physically defensible ranges until the resulting predictions gives the best possible fit to the observed data.
  • Conceptual Model: A hypothesis regarding the important factors that govern the behavior of an object or process of interest. This can be an interpretation or working description of the characteristics and dynamics of a physical system.
  • Deterministic Model: A model that provides a single solution for the variables being modeled. Because this type of model does not explicitly simulate the effects of data uncertainty or variability, changes in model outputs are solely due to changes in model components.
  • Empirical Model: An empirical model is one where the structure is determined by the observed statistical relationship among experimental data. These models can be used to develop relationships that are useful for forecasting and describing trends in behavior but they are not necessarily mechanistically relevant that is they don’t explain the real causes and mechanisms for the relationships.
  • Federate: an application that may be, or is coupled with other software applications under a Federation Object Model Document Data (FDD) and a runtime infrastructure (RTI).
  • Federation: a named set of federate applications and a common Federation Object Model that are used as a whole to achieve some specific objective.
  • Parameters: Terms in the model that are fixed during a model run or simulation but can be changed in different runs as a method for conducting sensitivity analysis or to achieve calibration goals.
  • Run Time Infrastructure (RTI): The software that provides common interface services during a HLA federation execution for synchronization and data exchange.
  • Sensitivity: The degree to which the model outputs are affected by changes in a selected input parameters.
  • Simulation Object Model (SOM): a specification of the types of information that an individual federate could provide to HLA federations as well as the information a federate could receive from other federates in HLA federations.
  • Statistical Models: Models obtained by fitting observational data to a mathematical function.
  • Stochastic Model: A model that includes variability in model parameters. This variability is a function of:
    • changing environmental conditions,
    • spatial and temporal aggregation within the model framework,
    • random variability.
  • Variable: A measured or estimated quantity which describes an object or can be observed in a system and which is subject to change.
  • Validation: Answers the questions “Is the science valid and does the model use current methods and techniques? Is the numerical model adequate to convey the science principles at the level of the question being asked? Is the model arriving at an acceptably accurate representation of the phenomenon being modeled?”
  • Verification: Does the code for the model run correctly and provide a mathematically correct answer? Do the algorithms being used accurately represent the mathematical function on the computer?

AcqLinks and References:

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