Optimal Experimental Design Methods

TopicLeading institutions, researchers & key papers

This cluster of papers focuses on the theory and application of experimental design and optimization methods, including Response Surface Methodology, Taguchi Method, multi-response optimization, Bayesian design, factorial designs, robust parameter design, and spatial analysis. The papers cover a wide range of applications in various fields such as engineering, manufacturing, biotechnology, and agriculture.

Works

IDs:OpenAlex

How has Optimal Experimental Design Methods's publication output changed over time?

ScholarIQpublication output · 2009–2020

Output grew100% over the shown period — from 1 works in 2009 to 2 in 2020.

20092012201320152016201720192020

What are the most-cited papers on Optimal Experimental Design Methods?

ScholarIQmost cited works

A robust desirability function method for multi-response surface optimization considering model uncertainty

Zhen He, Pengfei Zhu, Sung Hyun Park

S103321696. 2012136 Citations

A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP

Don van den Bergh, Johnny van Doorn, Maarten Marsman, Tim Draws, Erik–Jan van Kesteren, Koen Derks, Fabian Dablander, Quentin F. Gronau, Šimon Kucharský, Akash Raj, Alexandra Sarafoglou, Jan G. Voelkel, Angelika Marlene Stefan, Alexander Ly, Max Hinne, Dóra Matzke, Eric‐Jan Wagenmakers

2019112 CitationsOPEN ACCESS

Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method

An‐Da Li, Zhen He, Yang Zhang

Computers in Industry. 201659 Citations

Weibull and lognormal Taguchi analysis using multiple linear regression

Manuel R. Piña‐Monarrez, Jesús F. Ortiz-Yáñez

Reliability Engineering & System Safety. 201534 Citations

Simultaneous confidence intervals for ratios of means of several lognormal distributions: A parametric bootstrap approach

S. M. Sadooghi-Alvandi, Ahad Malekzadeh

S132362803. 201333 Citations