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contributor authorM. Krarti
contributor authorD. Cohen
contributor authorP. Curtiss
contributor authorJ. F. Kreider
date accessioned2017-05-08T23:57:45Z
date available2017-05-08T23:57:45Z
date copyrightAugust, 1998
date issued1998
identifier issn0199-6231
identifier otherJSEEDO-28279#211_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/121083
description abstractThis 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.
publisherThe American Society of Mechanical Engineers (ASME)
titleEstimation of Energy Savings for Building Retrofits Using Neural Networks
typeJournal Paper
journal volume120
journal issue3
journal titleJournal of Solar Energy Engineering
identifier doi10.1115/1.2888071
journal fristpage211
journal lastpage216
identifier eissn1528-8986
keywordsArtificial neural networks
keywordsStructures AND Energy conservation
treeJournal of Solar Energy Engineering:;1998:;volume( 120 ):;issue: 003
contenttypeFulltext


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