Response surfaces: designs and analyses
Response surfaces: designs and analyses
Nonlinear black-box modeling in system identification: a unified overview
Automatica (Journal of IFAC) - Special issue on trends in system identification
Proceedings of the 30th conference on Winter simulation
The main issues in nonlinear simulation metamodel estimation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation Modeling and Analysis
Simulation Modeling and Analysis
State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments
INFORMS Journal on Computing
Simulation metamodels for modeling output distribution parameters
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
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In this paper we propose a method to select an experimental design for estimating nonlinear simulation metamodels. Through a careful selection of design points, the method provides better fitting results than equally spaced point selection, with the same simulation effort. This method accounts for the input/output function of the simulation model, possibly a mathematical function nonlinear in the parameters. In spite of the fact that the paper concentrates on nonlinear regression metamodels, the method may be applied to other type of metamodels. The procedure is easy to construct (so, it is attractive to be used in practice) and focus on simulations scenarios in sub-regions where the input/output behavior has more interest. This procedure is illustrated with an application to a automobile parts factory. Finally, we draw some conclusions.area.