Examples of 'response surface' in a sentence
Meaning of "response surface"
Response surface: In statistics, a response surface is used to study the relationship between one or more predictor variables and a response variable. It is a mathematical model that predicts the response based on the input variables
How to use "response surface" in a sentence
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response surface
Response surface plot of beverage emulsion stability.
The optimization of polysaccharides hydrolysis was done by response surface methodology.
This response surface illustrates two important points.
Combinations of concentrations of medium additives were chosen to sample a response surface.
A response surface was constructed from the combined data.
More conventional design space appreciation and response surface fitting methodology is also described.
Adaptive response surface methodology can be used to solve this problem.
This study aimed to assess factors associated with periodontitis using response surface methodology.
Response surface methodology.
The experiments were performed using central composite rotational design applicable to response surface methodology.
The response surface is.
All the contour plots were generated using a response surface model derived from the raw data.
A response surface design was used to examine main effects and possible interactions.
The optimum values for ethanol and levan production were determined using response surface methodology rsm.
The response surface methodology technique was utilized to optimize the process conditions.
See also
Contour plots from this fitted response surface are the Isobols.
Response surface analysis is commonly used to summarize the results of a complex biological experiment.
IOSO Technology is based on the response surface methodology approach.
The response surface methodology and the desirability function was used to optimize the process.
This cooktop has Rapid Response surface units.
Methodology for response surface optimization of biodiesel blends synthesis castor beans and peanut.
Methods and formulas for the analysis of variance in Analyze Response Surface Design.
Doehlert designs are response surface modelling designs constructed from regular simplexes.
Therefore, this equation defines a response surface.
Some extensions of response surface methodology deal with the multiple response problem.
The study was a screening study, assuming a linear response surface.
Response surface methodology foud to be suitable method for investigating the amount of chocolate coating.
Therefore, the realization of a parametric study is required in order to build a response surface.
A response surface methodology was used to study bioemulsifier production by Candida lipolytica.
The estimated experimental space was visualized by contour- and response surface modelling.
Response surface methodology, response surface emulation.
A major contribution was made regarding surrogate models, also called response surface models.
In response surface designs, the columns for squared terms are not orthogonal to each other.
An analytic model is constructed from the experiment results, using response surface modelling.
In a response surface design, you designate a low level and a high level for each continuous factor.
The model obtained was validated through variance analysis ( anova ) and response surface methodology.
Response surface methodology ( RSM ) is typically used in the modeling and optimization of processes.
If a quadratic term is significant, you can conclude that the response surface features curvature.
In particular, response surface methodology ( RSM ) is presently a preferred approach to optimize culture growth parameters.
Only hypotheses 1 and 5 were supported by both the response surface fit and prediction tests.
Candida rugosa, lipase, response surface methodology, artificial neural network, unstructured kinetic modeling.
The extraction process was optimized using the response surface methodology ( RSM ).
The response surface model assumes a sigmoidal dose response for each compound defined by ( 2 ).
For the analysis was used pareto diagram, response surface graphs and process control graphs.
Panel B shows a three-dimensional representation of the response surface.
RSM simplified, optimizing processes using response surface methods for design of experiments.
A 2-level factorial screening design was followed by a confirming 3-level response surface design.
Two approaches were evaluated, response surface methodology ( neural networking ) and direct optimization.
As a first solution, we proposed an exploration approach based on the Response Surface Methodology.
A three-dimensional response surface is shown in Figure 4.
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