Building Energy Use Prediction and System Identification Using Recurrent Neural Networks
- 1 August 1995
- journal article
- Published by ASME International in Journal of Solar Energy Engineering
- Vol. 117 (3), 161-166
- https://doi.org/10.1115/1.2847757
Abstract
Following several successful applications of feedforward neural networks (NNs) to the building energy prediction problem (Wang and Kreider, 1992; JCEM, 1992, 1993; Curtiss et al., 1993, 1994; Anstett and Kreider, 1993; Kreider and Haberl, 1994) a more difficult problem has been addressed recently: namely, the prediction of building energy consumption well into the future without knowledge of immediately past energy consumption. This paper will report results on a recent study of six months of hourly data recorded at the Zachry Engineering Center (ZEC) in College Station, TX. Also reported are results on finding the R and C values for buildings from networks trained on building data.Keywords
This publication has 1 reference indexed in Scilit:
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