قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| تجربة عامل كسري تكيفية× | التصميم المركب المركزي× | |
|---|---|---|
| المجال | التصميم التجريبي | التصميم التجريبي |
| العائلة | Process / pipeline | Process / pipeline |
| سنة النشأة≠ | 1950s–1960s (classical FFD); adaptive extensions formalized in 1990s–2000s | 1951 |
| صاحب الطريقة≠ | Box, Hunter, and collaborators (adaptive/sequential extension of classical fractional factorial work) | George E. P. Box and K. B. Wilson |
| النوع≠ | Experimental design strategy | Response surface experimental design |
| المصدر التأسيسي≠ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 | Box, G. E. P., & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society: Series B, 13(1), 1–45. DOI ↗ |
| الأسماء البديلة | adaptive FFE, sequential fractional factorial design, adaptive screening design, adaptive factor screening | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| ذات صلة≠ | 2 | 3 |
| الملخص≠ | An adaptive fractional factorial experiment combines the resource-efficiency of fractional factorial designs with a sequential, data-driven strategy for selecting which factors and interactions to investigate next. Rather than committing all experimental runs upfront, the researcher analyses results from an initial fraction and uses those findings to guide subsequent rounds of experimentation — augmenting, folding, or redirecting the design until the active factors and optimal settings are identified with sufficient precision. | Central Composite Design (CCD) is a second-order response surface design that allows researchers to efficiently fit a full quadratic model relating multiple continuous input factors to one or more response variables. Introduced by Box and Wilson in 1951, it combines a factorial (or fractional factorial) core, axial (star) points, and center-point replicates into a single unified design, making it the most widely used design for process optimization in engineering, chemistry, and manufacturing. |
| ScholarGateمجموعة البيانات ↗ |
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