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Regression Tree-Based Methodology for Customizing Building Energy Benchmarks to Individual Commercial Buildings

Abstract According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (c... (more)
Created Date 2013
Contributor Kaskhedikar, Apoorva Prakash (Author) / Reddy, T. Agami (Advisor) / Bryan, Harvey (Committee member) / Runger, George (Committee member) / Arizona State University (Publisher)
Subject Architecture / Architectural engineering / Energy / Energy Benchmarking / Regression tree
Type Masters Thesis
Extent 154 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Built Environment 2013
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis