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- W2783470086 abstract "Discrete-event simulation as a methodology is often inextricably intertwined with many other forms of analytics. Source data often must be repaired or processed before being used (indirectly or directly) to characterize variation in a simulation model. Collection of simulated data needs to coordinate with and support the evaluation of performance metrics in the model. Or it might be necessary to integrate other analytics into a simulation model to capture particular complexities in the real world system. We show how SAS Simulation Studio, as an integral part of the SAS analytic ecosystem, enables you to tackle all of these challenges. You have full control over the use of input data and the creation of simulated data. Strong experimental design capabilities mean you can simulate for all needed scenarios. Additionally, you c an embed any SAS analytic program-optimization, data mining, or otherwise-directly into the execution of your simulation model." @default.
- W2783470086 created "2018-01-26" @default.
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- W2783470086 date "2017-12-01" @default.
- W2783470086 modified "2023-09-25" @default.
- W2783470086 title "Looking beyond the model: Data input, collection, and analysis with SAS® simulation studio" @default.
- W2783470086 doi "https://doi.org/10.1109/wsc.2017.8248151" @default.
- W2783470086 hasPublicationYear "2017" @default.
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