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  2. Verification and validation of computer simulation models

    en.wikipedia.org/wiki/Verification_and...

    Verification and validation of computer simulation models. Verification and validation of computer simulation models is conducted during the development of a simulation model with the ultimate goal of producing an accurate and credible model. [1][2] "Simulation models are increasingly being used to solve problems and to aid in decision-making.

  3. Modeling and simulation - Wikipedia

    en.wikipedia.org/wiki/Modeling_and_simulation

    Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making. [1][2] In the computer application of modeling and simulation a computer is used to ...

  4. Simulation - Wikipedia

    en.wikipedia.org/wiki/Simulation

    t. e. A simulation is an imitative representation of a process or system that could exist in the real world. [1][2][3] In this broad sense, simulation can often be used interchangeably with model. [2] Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key ...

  5. Computer simulation - Wikipedia

    en.wikipedia.org/wiki/Computer_simulation

    Computer simulation. A 48-hour computer simulation of Typhoon Mawar using the Weather Research and Forecasting model. Process of building a computer model, and the interplay between experiment, simulation, and theory. Computer simulation is the running of a mathematical model on a computer, the model being designed to represent the behaviour of ...

  6. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    The approximation of a normal distribution with a Monte Carlo method. Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle.

  7. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction. In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. [1] A solution is therefore an assignment of values to the variables that satisfies all constraints—that is, a point in ...

  8. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problem. Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables, which is solved by constraint satisfaction ...

  9. Constraint programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_programming

    Constraint programming. Constraint programming (CP)[1] is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constraint programming, users declaratively state the constraints on the feasible solutions for a set of decision variables.