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Informal methods of validation and verification are some of the more frequently used in modeling and simulation. They are called informal because they are more qualitative than quantitative. [1] While many methods of validation or verification rely on numerical results, informal methods tend to rely on the opinions of experts to draw a conclusion.
Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.
In the prototyping stage, engineers create actual working samples of the product they plan to produce. Engineering verification testing (EVT) is used on prototypes to verify that the design meets pre-determined specifications and design goals.
Cross validation is a method of model validation that iteratively refits the model, each time leaving out just a small sample and comparing whether the samples left out are predicted by the model: there are many kinds of cross validation. Predictive simulation is used to compare simulated data to actual data.
types of apparatus and measuring instrument (sometimes the specific device) required to conduct the test; sampling procedures (how samples are to be obtained and prepared, as well as the sample size) safety precautions; required calibrations and metrology systems; natural environment concerns and considerations; testing environment concerns and ...
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A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
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.