Estimation of Energy Savings for Building Retrofits Using Neural Networks
- 1 August 1998
- journal article
- Published by ASME International in Journal of Solar Energy Engineering
- Vol. 120 (3), 211-216
- https://doi.org/10.1115/1.2888071
Abstract
This paper overviews some applications of neural networks (NNs) to estimate energy and demand savings from retrofits of commercial buildings. First, a brief background information on NNs is provided. Then, three specific case studies are described to illustrate how and when NNs can be used successfully to determine energy savings due to the implementation of various energy conservation measures in existing commercial buildings.Keywords
This publication has 5 references indexed in Scilit:
- Heating and Cooling of BuildingsPublished by Informa UK Limited ,2016
- Statistical Analysis of Neural Networks as Applied to Building Energy PredictionJournal of Solar Energy Engineering, 2004
- Building Energy Use Prediction and System Identification Using Recurrent Neural NetworksJournal of Solar Energy Engineering, 1995
- The Appeal of Parallel Distributed ProcessingPublished by Elsevier BV ,1988
- Tests of Statistical Hypotheses Concerning Several Parameters When the Number of Observations is LargeTransactions of the American Mathematical Society, 1943