contributor author | M. Krarti | |
contributor author | D. Cohen | |
contributor author | P. Curtiss | |
contributor author | J. F. Kreider | |
date accessioned | 2017-05-08T23:57:45Z | |
date available | 2017-05-08T23:57:45Z | |
date copyright | August, 1998 | |
date issued | 1998 | |
identifier issn | 0199-6231 | |
identifier other | JSEEDO-28279#211_1.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/121083 | |
description 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Estimation of Energy Savings for Building Retrofits Using Neural Networks | |
type | Journal Paper | |
journal volume | 120 | |
journal issue | 3 | |
journal title | Journal of Solar Energy Engineering | |
identifier doi | 10.1115/1.2888071 | |
journal fristpage | 211 | |
journal lastpage | 216 | |
identifier eissn | 1528-8986 | |
keywords | Artificial neural networks | |
keywords | Structures AND Energy conservation | |
tree | Journal of Solar Energy Engineering:;1998:;volume( 120 ):;issue: 003 | |
contenttype | Fulltext | |