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Response surface methodology revisited. [PDF]

open access: yesProceedings of the Winter Simulation Conference, 2003
Response surface methodology (RSM) searches for the input combination that optimizes the simulation output. RSM treats the simulation model as a black box. Moreover, this paper assumes that simulation requires much computer time. In the first stages of its search, RSM locally fits first-order polynomials.
Angun, M.E.   +3 more
core   +7 more sources

Response Surface Methodology

open access: bronzeNippon Shokuhin Kagaku Kogaku Kaishi, 2013
Mario Shibata
  +5 more sources

Response surface methodology optimization of electrode modification parameters toward hydrazine electrooxidation on Pd/MWCNT/GCE

open access: yesMANAS: Journal of Engineering, 2023
In this study, MWCNT supported Pd (Pd/MWCNT) was synthesized by NaBH4 reduction method as catalyst for hydrazine electrooxidation reaction (HEOR). Characterization methods namely inductively coupled plasma mass spectrometry (ICP-MS), elemental mapping ...
Berdan Ulaş
doaj   +1 more source

Optimization of Spontaneous Fermentation Conditions of Kohlrabi by Response Surface Methodology

open access: yesFermentation, 2023
Kohlrabi is a valuable crop due to its substantial amount of macro- and micronutrients. It is mostly consumed in fresh form, as jam or fermented product.
Hatice Aybuke Karaoglan   +1 more
doaj   +1 more source

Response Surface Methodology for Optimization Membrane Disruption Using Thermolysis in Lipase Lk2 and Lk3

open access: yesJournal of Pure and Applied Microbiology, 2022
Lk2 and Lk3 were thermostable recombinant lipase and highly expressed in Escherichia coli BL21 (DE3). However, Lk2 and Lk3 accumulated as an inclusion body. To further characterize both recombinant lipases, the soluble enzyme must be obtained first. This
Titin Haryati   +3 more
doaj   +1 more source

Application of response surface methodology to stiffened panel optimization [PDF]

open access: yes, 2006
In a multilevel optimization frame, the use of surrogate models to approximate optimization constraints allows great time saving. Among available metamodelling techniques we chose to use Neural Networks to perform regression of static mechanical criteria,
Grihon, Stéphane   +2 more
core   +1 more source

Response Surface Methodology [PDF]

open access: yesSSRN Electronic Journal, 2014
This chapter first summarizes Response Surface Methodology (RSM), which started with Box and Wilson’s 1951 article on RSM for real, non-simulated systems. RSM is a stepwise heuristic that uses first-order polynomials to approximate the response surface locally.
openaire   +3 more sources

Response Surface Methodology Study on Magnetite Nanoparticle Formation under Hydrothermal Conditions

open access: yesNanomaterials and Nanotechnology, 2015
In a hydrothermal preparation of crystalline magnetite (Fe3O4) nanoparticles, the influence of the experimental parameters (initial molar ratio of ferrous/ferric ions, initial concentration of ferrous ions, and heating time), and their interactions, on ...
Naoya Mizutani   +2 more
doaj   +1 more source

Optimal design of single-tuned passive filters using response surface methodology [PDF]

open access: yes, 2015
This paper presents an approach based on Response Surface Methodology (RSM) to find the optimal parameters of the single-tuned passive filters for harmonic mitigation.
Abdel Aleem, SHE   +4 more
core   +1 more source

Combined beef thawing using response surface methodology

open access: yesCzech Journal of Food Sciences, 2016
Based on four thawing methods (still air, still water, ultrasonic wave, and microwave) and single-factor tests, we established a four-factor three-level response surface methodology for a regression model (four factors: pH, drip loss rate, cooking loss ...
Jiahui JIN   +9 more
doaj   +1 more source

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