Calculating Data Importance using Mutual Information for Engineering Design
Author(s)
Otero, Richard E.
Braun, Robert D.
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
As engineers examine larger coupled systems, computational complexity, available resources
and the lack of expert intuition create a need to understand the importance of
each link of data passed through an analysis. A better understanding and an automated
calculation of this data importance would enable an advance of the art for automated decomposition
and optimization methods. Larger coupled problems may, for instance, expand
beyond an expert's experience in manual decomposition. By automatically discovering the
importance and interrelated structure of a problem, low ranked data links might be temporarily
separated to decompose a problem into sub-problems. A better understanding
of the larger problem may also allow for organizational optimization around the coupled
sub-problems discovered by this method, that is theoretically grounded in Information
Theory.
Sponsor
Date
2010-09
Extent
Resource Type
Text
Resource Subtype
Paper
Rights Statement
Unless otherwise noted, all materials are protected under U.S. Copyright Law and all rights are reserved