Polynomial Response Surface Models is a mathematical modeling framework within response surface methodology that employs polynomial functions to approximate the relationship between input variables and a response variable, distinguished by its use of low-order polynomials to capture curvature and interaction effects in experimental data.
320
Publications
29.2K
Citations
812
Authors
347
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Publications per year
2017–2026
60
Variants
Polynomial Response Surfaces
Parents
Publications
320
Raymond H. Myers, Douglas C. Montgomery · IIE Transactions · 1996 · 3.8K citations
Response Surfaces: Designs and Analyses
Eric R. Ziegel, André I. Khuri, John A. Cornell · Technometrics · 1997 · 1.5K citations
1–5 of 320
Authors
812
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1–5 of 812
Institutions
347
University of Florida
Gainesville, United States
17 h-index
42 publications
1.9K citations
Virginia Tech
Blacksburg, United States
10 h-index
28 publications
813 citations
University of Michigan
Ann Arbor, United States
7 h-index
8 publications
394 citations
Pennsylvania State University
State College, United States
6 h-index
8 publications
1.5K citations
Universiti Putra Malaysia
Seri Kembangan, Malaysia
6 h-index
17 publications
494 citations
Central South University
Changsha, China
5 h-index
22 publications
539 citations
Langley Research Center
Hampton, United States
5 h-index
6 publications
2.3K citations
Indian Institute of Science Bangalore
Bengaluru, India
4 h-index
9 publications
195 citations
1–8 of 347
Venues
- Technometrics
24 publications · 4K citations
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- AIAA Journal
9 publications · 1.4K citations
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- Biometrics
7 publications · 881 citations
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- Journal of Quality Technology
7 publications · 474 citations
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- International Journal of Food Science & Technology
6 publications · 151 citations
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