@COMMENT This file was generated by bib2html.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <http://sourceforge.net/users/patstg/>
@COMMENT This file came from Sanjit Seshia's publication pages at http://www.eecs.berkeley.edu/~sseshia
@techreport{holcomb-tr09,
    Author = {Holcomb, Daniel and Li, Wenchao and Seshia, Sanjit A.},
    Title = {Algorithms for Green Buildings: Learning-Based Techniques for Energy Prediction and Fault Diagnosis},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2009},
    Month = {October},
    Number = {UCB/EECS-2009-138},
    Abstract = {We consider two problems in the design and operation of energy-efficient buildings. The first is the prediction
of energy consumption of a building from that of similar buildings in its geographical neighborhood. The second
problem concerns the localization of faults in building sub-systems with a focus on faults that lead to anomalous
energy consumption. For both problems, we propose algorithmic techniques based on machine learning to address
them. Simulation results using EnergyPlus show the promise of the proposed methods.},
}