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A Visual Analytics Based Decision Support Methodology For Evaluating Low Energy Building Design Alternatives


Abstract The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in ch... (more)
Created Date 2013
Contributor Dutta, Ranojoy (Author) / Reddy, T Agami (Advisor) / Runger, George (Committee member) / Addison, Marlin S (Committee member) / Arizona State University (Publisher)
Subject Architecture / Engineering / Energy / Building Design / High Performance / Random Forest / Satisficing / Visual Analytics
Type Masters Thesis
Extent 150 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note M.S. Architecture 2013
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis