Optimal Experimental Design

Ne-Zheng Sun () and Alexander Sun ()
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Ne-Zheng Sun: University of California at Los Angeles, Department of Civil and Environmental Engineering
Alexander Sun: University of Texas at Austin, Bureau of Economic Geology, Jackson School of Geosciences

Chapter 11 in Model Calibration and Parameter Estimation, 2015, pp 459-507 from Springer

Abstract: Abstract In environmental and water resource (EWR) engineering, different types of design problems exist, such as operation design, monitoring design, detection design, and remediation design. This chapter is devoted to the subject of experimental design for model calibration and parameter estimation. Experimental design plays a critical role in model construction because the reliability of a model is mainly dependent on the quantity and quality of data used for its calibration. In other words, the experimental design dictates how data should be collected in field campaigns and how many observations are needed. An optimal experimental design (OED), when it is executed, should provide the maximum amount of information with the minimum cost. Basic concepts, theories, and methods of OED are well established in statistics and have been applied to various scientific and engineering disciplines.

Keywords: Robust Design; Fisher Information Matrix; Inverse Solution; Submodular Function; Model Inversion (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4939-2323-6_11

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