Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks

The objective of this work was to use artificial neural networks for the long-term performance prediction of thermosiphonic type solar domestic water heating systems. Thirty systems have been tested and modeled according to the procedures outlines in the standard ISO 9459-2 at three locations in Gre...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Solar energy 2000-08, Vol.69 (2), p.163
Hauptverfasser:	Kalogirou, Soteris A, Panteliou, Sofia
Format:	Artikel
Sprache:	eng
Schlagworte:	Heating Solar energy Water
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page
container_issue	2
container_start_page	163
container_title	Solar energy
container_volume	69
creator	Kalogirou, Soteris A Panteliou, Sofia
description	The objective of this work was to use artificial neural networks for the long-term performance prediction of thermosiphonic type solar domestic water heating systems. Thirty systems have been tested and modeled according to the procedures outlines in the standard ISO 9459-2 at three locations in Greece.
format	Article
fullrecord	<record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_231702643</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>62941297</sourcerecordid><originalsourceid>FETCH-proquest_journals_2317026433</originalsourceid><addsrcrecordid>eNqNjUFuwjAQRS3USqS0dxixj2QntIZuKxCLLlmwQ1aYJE5jT5hxhHr7BtQDsHqL9_T_TGVmZU1uinf7pDKty3WuN8Vxrl5EOq2NNWubKTm0yIHEDy1FEOodw5kCSvIVXF1ChhZd8rEB-ZWEQT7hm2KTTybAgFwTBxcrhIHx7Kvkp5lRbr3j5GtfuR4ijnxHuhL_yKt6rl0v-PbPhVrutoevfT4wXcbp-tTRyHFSp6I0Vhcfq7J8KPoDgSROjw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>231702643</pqid></control><display><type>article</type><title>Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks</title><source>Access via ScienceDirect (Elsevier)</source><creator>Kalogirou, Soteris A ; Panteliou, Sofia</creator><creatorcontrib>Kalogirou, Soteris A ; Panteliou, Sofia</creatorcontrib><description>The objective of this work was to use artificial neural networks for the long-term performance prediction of thermosiphonic type solar domestic water heating systems. Thirty systems have been tested and modeled according to the procedures outlines in the standard ISO 9459-2 at three locations in Greece.</description><identifier>ISSN: 0038-092X</identifier><identifier>EISSN: 1471-1257</identifier><identifier>CODEN: SRENA4</identifier><language>eng</language><publisher>New York: Pergamon Press Inc</publisher><subject>Heating ; Solar energy ; Water</subject><ispartof>Solar energy, 2000-08, Vol.69 (2), p.163</ispartof><rights>Copyright Pergamon Press Inc. Aug 2000</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785</link.rule.ids></links><search><creatorcontrib>Kalogirou, Soteris A</creatorcontrib><creatorcontrib>Panteliou, Sofia</creatorcontrib><title>Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks</title><title>Solar energy</title><description>The objective of this work was to use artificial neural networks for the long-term performance prediction of thermosiphonic type solar domestic water heating systems. Thirty systems have been tested and modeled according to the procedures outlines in the standard ISO 9459-2 at three locations in Greece.</description><subject>Heating</subject><subject>Solar energy</subject><subject>Water</subject><issn>0038-092X</issn><issn>1471-1257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><recordid>eNqNjUFuwjAQRS3USqS0dxixj2QntIZuKxCLLlmwQ1aYJE5jT5hxhHr7BtQDsHqL9_T_TGVmZU1uinf7pDKty3WuN8Vxrl5EOq2NNWubKTm0yIHEDy1FEOodw5kCSvIVXF1ChhZd8rEB-ZWEQT7hm2KTTybAgFwTBxcrhIHx7Kvkp5lRbr3j5GtfuR4ijnxHuhL_yKt6rl0v-PbPhVrutoevfT4wXcbp-tTRyHFSp6I0Vhcfq7J8KPoDgSROjw</recordid><startdate>20000801</startdate><enddate>20000801</enddate><creator>Kalogirou, Soteris A</creator><creator>Panteliou, Sofia</creator><general>Pergamon Press Inc</general><scope>7SP</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope></search><sort><creationdate>20000801</creationdate><title>Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks</title><author>Kalogirou, Soteris A ; Panteliou, Sofia</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_2317026433</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Heating</topic><topic>Solar energy</topic><topic>Water</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kalogirou, Soteris A</creatorcontrib><creatorcontrib>Panteliou, Sofia</creatorcontrib><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Solar energy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kalogirou, Soteris A</au><au>Panteliou, Sofia</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks</atitle><jtitle>Solar energy</jtitle><date>2000-08-01</date><risdate>2000</risdate><volume>69</volume><issue>2</issue><spage>163</spage><pages>163-</pages><issn>0038-092X</issn><eissn>1471-1257</eissn><coden>SRENA4</coden><abstract>The objective of this work was to use artificial neural networks for the long-term performance prediction of thermosiphonic type solar domestic water heating systems. Thirty systems have been tested and modeled according to the procedures outlines in the standard ISO 9459-2 at three locations in Greece.</abstract><cop>New York</cop><pub>Pergamon Press Inc</pub></addata></record>
fulltext	fulltext
identifier	ISSN: 0038-092X
ispartof	Solar energy, 2000-08, Vol.69 (2), p.163
issn	0038-092X 1471-1257
language	eng
recordid	cdi_proquest_journals_231702643
source	Access via ScienceDirect (Elsevier)
subjects	Heating Solar energy Water
title	Thermosiphon solar domestic water heating systems: Long-term performance prediction using artifical neural networks
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T07%3A27%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Thermosiphon%20solar%20domestic%20water%20heating%20systems:%20Long-term%20performance%20prediction%20using%20artifical%20neural%20networks&rft.jtitle=Solar%20energy&rft.au=Kalogirou,%20Soteris%20A&rft.date=2000-08-01&rft.volume=69&rft.issue=2&rft.spage=163&rft.pages=163-&rft.issn=0038-092X&rft.eissn=1471-1257&rft.coden=SRENA4&rft_id=info:doi/&rft_dat=%3Cproquest%3E62941297%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=231702643&rft_id=info:pmid/&rfr_iscdi=true