Some New Three Level Designs for the Study of Quantitative Variables

By G. Box, D. W. Behnken. 1960

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1. M. Yolmeh
2. Wei Gong
3. Chen Wang
4. Reza Alizadeh
5. S. Jafari
6. Wei Chu
7. V. Chen
8. Chiyuan Miao

Citations in the corpus

• An evaluation of adaptive surrogate modeling based optimization with two benchmark problems (2014, background): “Among them, Full Factorial, Fractional Factorial (Box et al., 2005), Central Composite (Myers, 1971), BoxeBehnken (Box and Behnken, 1960), Monte Carlo, Latin Hypercube (McKay et al., 1979) and QuasiMonte Carlo (QMC) (Sobol',1967; Halton,1964) designs are themost widely used.”
• Bio compounds of edible mushrooms: in vitro antioxidant and antimicrobial activities (2019, unknown): “Optimization extraction parameters of TPC of each mushroom were performed using a Box-Behnken design (Box & Behnken, 1960).”
• Managing computational complexity using surrogate models: a critical review (2020, background): “…including factorial designs, fractional factorial designs (Gunst and Mason 2009; Montgomery 2017), central composite designs (Mont-gomery 2017; Box and Behnken 1960), orthogonal arrays (Hedayat et al. 2012; Dey 1985; Montgomery 2017), D-optimal (Myers et al. 2016), Placket-Burman (Gustafsson…”
• Design and Analysis of Experiments (2001, methodology): “As illustrated by Box and Behnken (1960), a Box– Behnken design can be constructed from a composition of a balanced incomplete block design inb 6 blocks of sizek 2 and a 22 factorial design as follows.”
• Reliability in composites – a selective review and survey of current development (2012, methodology): “As states in Gomes and Awruch [85], the main point resides into adjust the polynomials to the LSF using the sample points, by using some of the several fitting techniques such as (a) the central composite design [91,92], (b) the fractional factorial design [93], (c) the random design, (d) the partia”
• Response-Surface Methods in R, Using rsm (2009, methodology): “For example, here we generate a 3-factor Box-Behnken design (Box and Behnken 1960) One of the most popular response-surface designs is the central-composite design (CCD), due to Box and Wilson (1951).”
• Effects of culture conditions on the mycelial growth and bioactive metabolite production in submerged culture of Cordyceps militaris (2007, methodology): “Box–Behnken design (BBD) [3] was conducted to optimize cordycepin production by C.”
• Model-Dependent Variance Inflation Factor Cutoff Values (2002, methodology): “A 15-run Box–Behnken design (see [6] ) was designed for three variables thought to have an impact on maximum IGA (Max IGA).”