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Critical reviews in environmental science and technology, 2020
Nowadays, water pollution has been considered a global concern on environmental sustainability, calling for high-performance materials in effective pollution treatments.
Z. Anfar +6 more
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Nowadays, water pollution has been considered a global concern on environmental sustainability, calling for high-performance materials in effective pollution treatments.
Z. Anfar +6 more
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The MM-Estimator in Response Surface Methodology [PDF]
Quality Engineering, 2005 The MM-estimator is proposed to model the responses in response surface methodology (RSM). This robust regression technique allows better optimal setting in dual-response and multiple-response surface optimization when responses are nonnormal and/or con..
Heng Chin Low, C.K. Ch'ng, S. H. Quah
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2018
Response surface methodology or in short RSM is a collection of mathematical and statistical tools and techniques that are useful in developing, understanding, and optimizing processes and products. Using this methodology, the responses that are influenced by several variables can be modeled, analyzed, and optimized.
Dharmaraja Selvamuthu, Dipayan Das
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Response surface methodology or in short RSM is a collection of mathematical and statistical tools and techniques that are useful in developing, understanding, and optimizing processes and products. Using this methodology, the responses that are influenced by several variables can be modeled, analyzed, and optimized.
Dharmaraja Selvamuthu, Dipayan Das
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2017
Experiments for fitting a predictive model involving several continuous variables are known as response surface experiments. The objectives of response surface methodology include the determination of variable settings for which the mean response is optimized and the estimation of the response surface in the vicinity of this good location.
Angela M. Dean +2 more
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Experiments for fitting a predictive model involving several continuous variables are known as response surface experiments. The objectives of response surface methodology include the determination of variable settings for which the mean response is optimized and the estimation of the response surface in the vicinity of this good location.
Angela M. Dean +2 more
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2004
Abstract : There is a problem faced by experimenters in many technical fields, where, in general, the response variable of interest is y, and there is a set of predictor variables x1, x2,...xk. For example, in Dynamic Network Analysis (DNA) Response Surface Methodology (RSM) might be useful for sensitivity analysis of various DNA measures for different
Jeff Reminga +2 more
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Abstract : There is a problem faced by experimenters in many technical fields, where, in general, the response variable of interest is y, and there is a set of predictor variables x1, x2,...xk. For example, in Dynamic Network Analysis (DNA) Response Surface Methodology (RSM) might be useful for sensitivity analysis of various DNA measures for different
Jeff Reminga +2 more
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Response Surface Methodology: 1966-1988
Technometrics, 1989Response sarfxe methodology (RSM) is a collection of tools developed in the 1950s for the purpose of determining optimum operating conditions in applications in the chemical industry. This article reviews the progrrss of RSM in the general areas of experimental design and analysis and indicates how its role has been affected by advanccs in other fields
Raymond H. Myers +3 more
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New approach for response surface methodology
SPIE Proceedings, 2001Modified Response Surface Methodology (MRSM) is proposed for the approximation of numerical simulation results. This approach is based on the parametric statistics methods. The tensor products or Chebyshev's polynomials are used for the non-linear regression series in order to decrease the mean- square error.
Alexander A. Kouleshoff +1 more
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Comparisons with the best in response surface methodology
Statistics & Probability Letters, 1999Confidence intervals about the difference in mean responses at the stationary point and alternate points are constructed based on the proposed delta method and F-projection method. Results of a simulation study to compare coverage probabilities and interval widths are discussed.
Linda J. Moore, Ping Sa
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Introduction to Response-Surface Methodology
2017Until now, we have considered how a dependent variable, yield, or response depends on specific levels of independent variables or factors. The factors could be categorical or numerical; however, we did note that they often differ in how the sum of squares for the factor is more usefully partitioned into orthogonal components.
Giovana B. Celli +2 more
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Optimization by the Response Surface Methodology of Color
2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), 2020The work presented in this paper concerns the optimization of the color of wastewater by the tannery, under the effects of factors that have significant impacts. The aim is to reduce the pollution caused by colored industrial waste from the tannery. This study is based on the application of the experiments design, during the physicochemical treatment ...
El Houssine Chatri +3 more
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