This book presents modern applications of Response Surface Methodology (RSM) in engineering science. Chapters discuss such topics as machine learning models of RSM as well as potential applications of RSM in industries such as pharmaceuticals, agriculture, textiles, and food, among others
This introduction to the R package rsm is a modified version of Lenth (2009), pub-lished in the Jour...
Several chemical and biological processes have been investigated and predicted using Response Surfac...
In any product and process optimization, the use of the traditional OFAT approach examines only one...
In this review chapter, the authors presented a systematic exposition to the concept of Response Sur...
Traditional response surface methodology (RSM) has utilized the ordinary least squared (OLS) techniq...
The possibilities of the Response Surface Methodology (RSM) has been explored within the ambit o
3noResponse Surface Methods (RSMs) are statistical and numerical models that approximate the relati...
Response Surface Methodology (RSM) is an amount of mathematical and statistical techniques used to s...
The possibilities of the Response Surface Methodology (RSM) has been explored within the ambit of Sc...
Response Surface Methodology (RSM) is an optimization tool that can identify interrelationship betwe...
This article describes the recent package rsm, which was designed to provide R support for standard ...
Response Surface Methodology (RSM) is an optimization tool that can identify interrelationship betwe...
Response Surface Models (RSM) based on data from designed numerical experiments are useful as approx...
This chapter first summarizes Response Surface Methodology (RSM), which started with Box and Wilson’...
Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into...
This introduction to the R package rsm is a modified version of Lenth (2009), pub-lished in the Jour...
Several chemical and biological processes have been investigated and predicted using Response Surfac...
In any product and process optimization, the use of the traditional OFAT approach examines only one...
In this review chapter, the authors presented a systematic exposition to the concept of Response Sur...
Traditional response surface methodology (RSM) has utilized the ordinary least squared (OLS) techniq...
The possibilities of the Response Surface Methodology (RSM) has been explored within the ambit o
3noResponse Surface Methods (RSMs) are statistical and numerical models that approximate the relati...
Response Surface Methodology (RSM) is an amount of mathematical and statistical techniques used to s...
The possibilities of the Response Surface Methodology (RSM) has been explored within the ambit of Sc...
Response Surface Methodology (RSM) is an optimization tool that can identify interrelationship betwe...
This article describes the recent package rsm, which was designed to provide R support for standard ...
Response Surface Methodology (RSM) is an optimization tool that can identify interrelationship betwe...
Response Surface Models (RSM) based on data from designed numerical experiments are useful as approx...
This chapter first summarizes Response Surface Methodology (RSM), which started with Box and Wilson’...
Response surface methodology (RSM) is a very efficient tool to provide a good practical insight into...
This introduction to the R package rsm is a modified version of Lenth (2009), pub-lished in the Jour...
Several chemical and biological processes have been investigated and predicted using Response Surfac...
In any product and process optimization, the use of the traditional OFAT approach examines only one...
DOI
Add to ORKG