Response Surface Methodology at Irregular Grids Based on Voronoi Scheme with Neural Network Approximator

Jacek Pietraszek

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Optimal Experimental Design Methods Neural Networks and Applications Advanced Multi-Objective Optimization Algorithms

Abstract

Traditional response surface methodology is based on polynomial approximators and designs prepared according to statistical requirements. In those cases when response surface cannot be modelled with single polynomial plane, a neural network approximator should be used. These approximators require a different design identification procedure. The author proposes to apply well-known Voronoi scheme to construct iteratively a new design.

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1951A Stochastic Approximation Method 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments 1988Empirical Model Building and Response Surfaces 1991Quality Engineering Using Robust Design 1990Quality Engineering Using Robust Design 1952Stochastic Estimation of the Maximum of a Regression Function 1988Empirical Model-Building and Response Surfaces.1990Statistical design and analysis of experiments: with applications to engineering and science

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