Title: A fuzzy set theoretic approach to validate simulation models
Authors: Martens, Jurgen ×
Put, Ferdinand
Kerre, Etienne #
Issue Date: 2006
Publisher: Assoc computing machinery
Series Title: Acm transactions on modeling and computer simulation vol:16 issue:4 pages:375-398
Abstract: We develop a new approach to the validation of simulation models by exploiting elements from fuzzy set theory and machine learning. A fuzzy resemblance relation concept is used to set up a mathematical framework for measuring the degree of similarity between the input-output behavior of a simulation model and the corresponding behavior of the real system. A neuro-fuzzy inference algorithm is employed to automatically learn the required resemblance relation from real and simulated data. Ultimately, defuzzification strategies are applied to obtain a coefficient on the unit interval that characterizes the degree of model validity. An example in the airline industry illustrates the practical application of this methodology.
ISSN: 1049-3301
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Management Informatics (LIRIS), Leuven
× corresponding author
# (joint) last author

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