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Showing 1 to 20 of 356 for “"response surface"”.
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Sequential robust response surface strategy
General Response Surface Methodology involves the exploration of some response variable which is a function of other controllable variables. Many criteria exist for selecting an experimental design for the controllable variables. A good choice of a design is one that may not be optimal in a single …
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Semiparametric Techniques for Response Surface Methodology
… statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree …
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Outliers and robust response surface designs
A commonly occurring problem in response surface methodology is that of inconsistencies in the response variable. These inconsistencies, or maverick observations, are referred to here as outliers. Many models exist for describing these outliers. Two of these models, the mean shift and the variance …
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Response Surface Modelling of Monte-Carlo Fire Data
… structural reliability context is that of the response surface method. It consists in representing each output parameter by a nonlinear function of the input parameters. Usually, a quadratic function of the input parameters turns out to be sufficient. Fitting of the response surface is carried …
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Response surface study of a characteristic chemical plant
"Study of the return on investment response surface of a characteristic chemical plant indicates unimodality in the valid region, but the optimum design condition with this response surface is strongly affected by the correlation used for the investment. The method used for the design of this type …
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Response Surface Method for Time-Variant Reliability Analysis
… is presented in this study. The method uses response surface methodology and the fast integration scheme developed by Wen and Chen (1987). The mean and coefficient of variation of the maximum response of the structure are modeled by second order polynomials fitted using central composite …
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Response surface methods applied to submarine concept exploration
… thesis examines a statistical technique called Response Surface Methods (RSM). The purpose of RSM is to lead to an understanding of the relationship between the input (factors) and output (response) variables, often to further the optimization of the underlying process. The RSM approach allows …
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Optimality criteria applied to certain response surface designs
… polynomial model was shown to be important in Response Surface Methodology (RSM). This led naturally to designing RSM experiments for best estimation of these coefficients as a primary goal. A design criterion, D<sub>S</sub>-optimality, was applied to several classes of RSM designs to find …
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Some optimization procedures used in response surface methodology
… survey into selected optimization topics of response surface methodology. In a typical response surface problem one of the main problems to be solved is to find those levels of the controllable variables to provide an optimum response such as highest yield or lowest cost. Several methods for …
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A new estimation procedure for response surface models
… have been made to find an estimator of a response which will have a smaller integrated mean square error than existing procedures. In this work another such attempt is made by introducing a shrinkage procedure. Suppose the true functional relationship between a response η and ρ independent …
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Response surface designs for the detection of model inadequacy
… it is tentatively assumed that the experimental response is related to some independent variables, x, by η₁(x) = x₁’ β₁. However, there is frequently some doubt whether this model adequately approximates the true response function, so a lack of fit test is used as part of the analysis. We suppose …
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Self learning strategies for experimental design and response surface optimization
… for optimization of different types of response surfaces for industrial experiments with noise, high experimentation cost, and requiring high design optimization performance. The proposed approach is a sequential adaptive experimentation approach which combines concepts from nonlinear …
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An Integrated Probability-Based Approach for Multiple Response Surface Optimization
… at the same time. Correlation between responses and model parameter uncertainty demands extra scrutiny and prevents practitioners from studying responses in isolation. Like any other multi-objective problem, multi-response optimization problem requires trade-offs and compromises, which …
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Graphical assessment of the prediction capability of response surface designs
A response surface analysis is concerned with the exploration of a system in order to determine the behavior of the response of the system as levels of certain factors which influence the response are changed. It is often of particular interest to predict the response in some region of the …
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Response surface designs and analysis for bi-randomization error structures
… randomizations may dictate the necessity to run response surface experiments in a bi-randomization error control format of which the split plot design is a special case. A bi-randomization scheme allows for certain factor levels to be applied at random to large experimental units with the …
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Structural Optimization of Bell Crank using Adaptive Response Surface Optimization
… avenue explored in this study is the adaptive response surface optimization process. The adaptive response surface optimization method involves the adaptive control of samples selected through the design of experiments and empirical models constructed via the response surface methodology, with …
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The use of correlated simulation experiments in response surface optimization
Response surface methodology (RSM) provides a useful framework for the optimization of stochastic simulation models. The sequential experimentation and model fitting procedures of RSM enable prediction of the response and location of the optimum operating conditions. In a simulation environment, …
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A response surface for the complex modulus of composite materials
… program resulted in the development of response surfaces for the complex moduli of composite materials.
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Precision of the path of steepest ascent in response surface methodology
… the precision of the path of steepest ascent in response surface methodology to cover situations with correlated and heteroscedastic responses, including the important class of generalised linear models. It is shown how the eigenvalues of a certain matrix can be used to express the proportion of …
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A response surface model of the air quality impacts of aviation
… pollutant concentrations. In this thesis, a response surface model (RSM) is developed for the high-fidelity, but time-consuming, Community Multiscale Air Quality (CMAQ) simulation system. The RSM relates changes in aviation emissions in the United States to changes in ambient concentrations …
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