Improving Innovation from Science Using Kernel Tree Methods as a Precursor to Designed Experimentation

Improving Innovation from Science Using Kernel Tree Methods as a Precursor to Designed Experimentation

A key challenge in applied science when planning a designed experiment is to determine the aliasing structure of the interaction effects and selecting the appropriate levels for the factors. In this study, kernel tree methods are used as precursors to identify significant interactions and levels of...

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Bibliographic Details
Main Authors: Timothy M. Young, Robert A. Breyer, Terry Liles, Alexander Petutschnigg
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Applied Sciences
Subjects:
kernel tree methods
interaction effects
aliasing structure
design experimentation
response surface methods
Online Access:https://www.mdpi.com/2076-3417/10/10/3387

Internet

https://www.mdpi.com/2076-3417/10/10/3387

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