Sparse polynomial chaos expansions: Literature survey and benchmark
Sparse polynomial chaos expansions (PCE) are a popular surrogate modelling method that
takes advantage of the properties of PCE, the sparsity-of-effects principle, and powerful …
takes advantage of the properties of PCE, the sparsity-of-effects principle, and powerful …
Design of experiments and regression modelling in food flavour and sensory analysis: A review
P Yu, MY Low, W Zhou - Trends in Food Science & Technology, 2018 - Elsevier
Background Food sensory science and flavour analysis are key processes in new product
development, and is essential in understanding consumers by bridging the gap between …
development, and is essential in understanding consumers by bridging the gap between …
Sensor selection via convex optimization
S Joshi, S Boyd - IEEE Transactions on Signal Processing, 2008 - ieeexplore.ieee.org
We consider the problem of choosing a set of k sensor measurements, from a set of m
possible or potential sensor measurements, that minimizes the error in estimating some …
possible or potential sensor measurements, that minimizes the error in estimating some …
Matrix algebra
JE Gentle - Springer texts in statistics, Springer, New York, NY, doi, 2007 - Springer
Vectors and matrices are useful in representing multivariate numeric data, and they occur
naturally in working with linear equations or when expressing linear relationships among …
naturally in working with linear equations or when expressing linear relationships among …
Near-optimal sensor placements in gaussian processes
When monitoring spatial phenomena, which are often modeled as Gaussian Processes
(GPs), choosing sensor locations is a fundamental task. A common strategy is to place …
(GPs), choosing sensor locations is a fundamental task. A common strategy is to place …
Least squares polynomial chaos expansion: A review of sampling strategies
As non-intrusive polynomial chaos expansion (PCE) techniques have gained growing
popularity among researchers, we here provide a comprehensive review of major sampling …
popularity among researchers, we here provide a comprehensive review of major sampling …
Optimization of designed experiments based on multiple criteria utilizing a Pareto frontier
L Lu, CM Anderson-Cook, TJ Robinson - Technometrics, 2011 - Taylor & Francis
Balancing competing objectives to select an optimal design of experiments involves flexibly
combining measures to select a winner. The Pareto front approach for simultaneously …
combining measures to select a winner. The Pareto front approach for simultaneously …
An algorithmic approach to constructing supersaturated designs
NK Nguyen - Technometrics, 1996 - Taylor & Francis
Supersaturated designs are very cost-effective to scientists and engineers at the primary
stage of scientific investigation. This article describes a method of constructing …
stage of scientific investigation. This article describes a method of constructing …
[图书][B] An introduction to optimal designs for social and biomedical research
MPF Berger, WK Wong - 2009 - books.google.com
The increasing cost of research means that scientists are in more urgent need of optimal
design theory to increase the efficiency of parameter estimators and the statistical power of …
design theory to increase the efficiency of parameter estimators and the statistical power of …
Sparse polynomial chaos expansions via compressed sensing and D-optimal design
In the field of uncertainty quantification, sparse polynomial chaos (PC) expansions are
commonly used by researchers for a variety of purposes, such as surrogate modeling. Ideas …
commonly used by researchers for a variety of purposes, such as surrogate modeling. Ideas …