Add to ORKGInterpolation and smoothing methods form the basis of simulation metamodeling. In high dimensional metamodeling problems, larger numbers of design points are needed to build an accurate metamodel. This paper introduces a procedure to implement a smoothing method called Moving Least Squares regression in high dimensional metamodeling problems with a large number of design points. We test the procedure with two queueing examples: a multi-product M/G/1 queue and a multi-product tandem Jackson network.
12 Linear regression metamodels have been widely used to explain the behavior of computer simulation...
This paper suggests a methodology for developing a simulation metamodel involving both quantitative ...
Linear regression metamodels have been widely used to explain the behavior of computer simulation mo...
The aim of this study is twofold. The first is to estimate a metamodel for a time-shared computer sy...
This chapter surveys two methods for the optimization of real-world systems that are modelled throug...
The paper describes a new methodology for the emulation of high order, dynamic simulation models. Th...
Surrogate-based optimization has become a major field in engineering design, due to its capacity to ...
A major challenge of metamodeling in simulation-based engineering design optimization is to handle t...
This paper introduces a new hierarchical metamodeling scheme for large scale computer simulations. T...
This paper introduces a technique for reducing the sampling size necessary to explore a design space...
This expository paper discusses the relationships among metamodels, simulation models, and problem e...
Frequently, the main objective of statistically designed simulation experiments is to estimate and v...
This article reviews the design and analysis of simulation experiments. It focusses on analysis via ...
ABSTRACT: In some studies requiring predictive numerical models, it can be advantageous to replace c...
Despite the advances in computer capacity, the enormous computational cost of complex engineering si...
12 Linear regression metamodels have been widely used to explain the behavior of computer simulation...
This paper suggests a methodology for developing a simulation metamodel involving both quantitative ...
Linear regression metamodels have been widely used to explain the behavior of computer simulation mo...
The aim of this study is twofold. The first is to estimate a metamodel for a time-shared computer sy...
This chapter surveys two methods for the optimization of real-world systems that are modelled throug...
The paper describes a new methodology for the emulation of high order, dynamic simulation models. Th...
Surrogate-based optimization has become a major field in engineering design, due to its capacity to ...
A major challenge of metamodeling in simulation-based engineering design optimization is to handle t...
This paper introduces a new hierarchical metamodeling scheme for large scale computer simulations. T...
This paper introduces a technique for reducing the sampling size necessary to explore a design space...
This expository paper discusses the relationships among metamodels, simulation models, and problem e...
Frequently, the main objective of statistically designed simulation experiments is to estimate and v...
This article reviews the design and analysis of simulation experiments. It focusses on analysis via ...
ABSTRACT: In some studies requiring predictive numerical models, it can be advantageous to replace c...
Despite the advances in computer capacity, the enormous computational cost of complex engineering si...
12 Linear regression metamodels have been widely used to explain the behavior of computer simulation...
This paper suggests a methodology for developing a simulation metamodel involving both quantitative ...
Linear regression metamodels have been widely used to explain the behavior of computer simulation mo...