Comparison of experimental designs using neural networks

✍ Scribed by Yun Lin; Zisheng Zhang; Jules Thibault

• Publisher: John Wiley and Sons
• Year: 2009
• Tongue: English
• Weight: 123 KB
• Volume: 87
• Category: Article
• ISSN: 0008-4034
• DOI: 10.1002/cjce.20233

✦ Synopsis

Abstract

Experimental designs were compared using stacked‐layer feed‐forward neural networks. Several traditional three‐level designs and uniform designs were investigated using three‐factor linear and nonlinear models. The prediction error was found to be inversely proportional to the number of experiments. Uniform designs displayed better performance than traditional three‐level designs for the same number of experiments. The sum of squares of prediction errors was generally smaller for uniform designs. The performance difference between three‐level designs and uniform designs was attributed to the number of factor levels. This was confirmed by further investigation on random designs with more factor levels.