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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis
The Summer Undergraduate Research Fellowship (SURF) Symposium
Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …
Imputing Characteristic Values Of Agricultural "Seed-Stock", Bbryan E. Melton, W. Arden Colette, Richard L. Willham
Imputing Characteristic Values Of Agricultural "Seed-Stock", Bbryan E. Melton, W. Arden Colette, Richard L. Willham
Conference on Applied Statistics in Agriculture
Statistical methods of regression and mathematical (linear) programming are employed to combine principles of economics and genetics in a conceptual, multi-step, model of valuation for biotechnical change. The resulting model has the capacity to estimate the value of changes in specific characteristics for specific production environments, whether those changes are accomplished by traditional plant and animal breeding methods or by genetic engineering. The application of the model is illustrated with an example of commercial cow-calf production under conditions typical of the Texas Panhandle using a total of 32 breed groups.
Analysis Of Repeated Measures Data, Ramon C. Littell
Analysis Of Repeated Measures Data, Ramon C. Littell
Conference on Applied Statistics in Agriculture
Data with repeated measures occur frequently in agricultural research. This paper is a brief overview of statistical methods for repeated measures data. Statistical analysis of repeated measures data requires special attention due to the correlation structure, which may render standard analysis of variance techniques invalid. For balanced data, multivariate analysis of variance methods can be employed and adjustments can be applied to univariate methods, as means of accounting for the correlation structure. But these analysis of variance methods do not apply readily with unbalanced data, and they overlook the regression on time. Regression curves for treatment groups can be obtained …