Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/17956
Title: | Artificial neural networks in energy applications in buildings |
Authors: | Kalogirou, Soteris A. |
Major Field of Science: | Engineering and Technology |
Field Category: | Environmental Engineering |
Keywords: | Artificial neural networks;Energy prediction;Building applications |
Issue Date: | Jul-2006 |
Source: | International Journal of Low Carbon Technologies, 2006, vol. 1, no. 3, pp. 201–216 |
Volume: | 1 |
Issue: | 3 |
Start page: | 201 |
End page: | 216 |
Journal: | International Journal of Low Carbon Technologies |
Abstract: | Artificial neural networks (ANNs) are nowadays accepted as an alternative technology offering a way to tackle complex and ill-defined problems. They are not programmed in the traditional way but they are trained using past history data representing the behaviour of a system. They have been used in a number of diverse applications. Results presented in this paper are testimony to the potential of artificial neural networks as a design tool in many areas of building services engineering. |
URI: | https://hdl.handle.net/20.500.14279/17956 |
ISSN: | 17481317 |
DOI: | 10.1093/ijlct/1.3.201 |
Rights: | © Manchester University Press 2006 |
Type: | Article |
Affiliation : | Higher Technical Institute Cyprus |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
Files in This Item:
File | Description | Size | Format | |
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1-3-201.pdf | Fulltext | 224.47 kB | Adobe PDF | View/Open |
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