From robust chip to smart building: CAD algorithms and methodologies for uncertainty analysis of building performance

Published

Conference Paper

© 2015 IEEE. Buildings consume about 40% of the total energy use in the U.S. and, hence, accurately modeling, analyzing and optimizing building energy is considered as an extremely important task today. Towards this goal, uncertainty/sensitivity analysis has been proposed to identify the critical physical and environmental parameters contributing to building energy consumption. In this paper, we propose to apply sparse regression techniques to uncertainty/sensitivity analysis of smart buildings. We consider the orthogonal matching pursuit (OMP) algorithm as a case study to demonstrate its superior efficacy over other conventional approaches. Experimental results reveal that OMP achieves up to 18.6× runtime speedups over the conventional least-squares fitting method without surrendering any accuracy.

Full Text

Duke Authors

Cited Authors

  • Chen, X; Li, X; Tan, SXD

Published Date

  • January 5, 2016

Published In

  • 2015 Ieee/Acm International Conference on Computer Aided Design, Iccad 2015

Start / End Page

  • 457 - 464

International Standard Book Number 13 (ISBN-13)

  • 9781467383882

Digital Object Identifier (DOI)

  • 10.1109/ICCAD.2015.7372605

Citation Source

  • Scopus