@inproceedings{1f44760d7da44c2bb6b834349ddd0796,
title = "Sensitivity Analysis and Uncertainty Quantification of State-Based Discrete-Event Simulation Models Through a Stacked Ensemble of Metamodels",
abstract = "Realistic state-based discrete-event simulation models are often quite complex. The complexity frequently manifests in models that (a) contain a large number of input variables whose values are difficult to determine precisely, and (b) take a relatively long time to solve. Traditionally, models that have a large number of input variables whose values are not well-known are understood through the use of sensitivity analysis (SA) and uncertainty quantification (UQ). However, it can be prohibitively time consuming to perform SA and UQ. In this work, we present a novel approach we developed for performing fast and thorough SA and UQ on a metamodel composed of a stacked ensemble of regressors that emulates the behavior of the base model. We demonstrate the approach using a previously published botnet model as a test case, showing that the metamodel approach is several orders of magnitude faster than the base model, more accurate than existing approaches, and amenable to SA and UQ.",
keywords = "Emulators, Metamodels, Optimization, Reliability models, Security models, Sensitivity analysis, Surrogate models, Uncertainty quantification",
author = "Michael Rausch and Sanders, {William H.}",
note = "Funding Information: Acknowledgements. The authors would like to thank Jenny Applequist, Lowell Rausch, and the reviewers for their feedback on the paper. This material is based upon work supported by the Maryland Procurement Office under Contract No. H98230-18-D-0007. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Maryland Procurement Office. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 17th International Conference on Quantitative Evaluation Systems, QEST 2020 ; Conference date: 31-08-2020 Through 03-09-2020",
year = "2020",
doi = "10.1007/978-3-030-59854-9_20",
language = "English (US)",
isbn = "9783030598532",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "276--293",
editor = "Marco Gribaudo and Jansen, {David N.} and Anne Remke",
booktitle = "Quantitative Evaluation of Systems - 17th International Conference, QEST 2020, Proceedings",
address = "Germany",
}