Tutorial: Basics of Metamodeling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Metamodels are fast-to-compute mathematical models that are designed to mimic the input-output behavior of discrete-event or other complex simulation models. Linear regression metamodels have the longest history, but other model forms include Gaussian process regression and neural networks. This introductory tutorial highlights basic issues in choosing a metamodel type and specific form, and making simulation runs to fit the metamodel. The tutorial ends with a warning on potential pitfalls, and suggestions on further reading to expand your knowledge of metamodeling.

Original languageEnglish (US)
Title of host publication2023 Winter Simulation Conference, WSC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1516-1530
Number of pages15
ISBN (Electronic)9798350369663
DOIs
StatePublished - 2023
Event2023 Winter Simulation Conference, WSC 2023 - San Antonio, United States
Duration: Dec 10 2023Dec 13 2023

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

Conference2023 Winter Simulation Conference, WSC 2023
Country/TerritoryUnited States
CitySan Antonio
Period12/10/2312/13/23

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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