Impact of weather inputs on heating plant - Agglomeration modeling

Vařacha, Pavel

dc.title	Impact of weather inputs on heating plant - Agglomeration modeling	en
dc.contributor.author	Vařacha, Pavel
dc.relation.ispartof	NN'09: Proceedings of the 10th WSEAS International Conference on Neural Networks
dc.identifier.isbn	978-960-474-065-9
dc.date.issued	2009
dc.citation.spage	159
dc.citation.epage	162
dc.event.title	10th WSEAS International Conference on Neural Networks
dc.event.location	Prague
utb.event.state-en	Czech Republic
utb.event.state-cs	Česká republika
dc.event.sdate	2009-03-23
dc.event.edate	2009-03-25
dc.type	conferenceObject
dc.language.iso	en
dc.publisher	World Scientific and Engineering Academy and Society (WSEAS)	en
dc.relation.uri	http://www.wseas.us/e-library/conferences/2009/prague/NEURAL/NEURAL27.pdf
dc.subject	artificial neural network	en
dc.subject	modeling	en
dc.subject	heting plant	en
dc.subject	weather	en
dc.subject	humidity	en
dc.subject	wind speed	en
dc.description.abstract	This article describes performance of artificial neural network (ANN) oil modeling interface between a heating plant and an agglomeration. ANN perform one step ahead prediction of water temperature returned from agglomeration based on input water temperature, flow and atmospheric temperature in past 24 hours. Usage of ANN In two factual heating plant in Komorany and Detmarovice, Czech Republic. Main concern of the article is to explore possibility Of tuning ANN accuracy by additional Inputs for humidity and wind speed.	en
utb.faculty	Faculty of Applied Informatics
dc.identifier.uri	http://hdl.handle.net/10563/1001833
utb.identifier.rivid	RIV/70883521:28140/09:63508015!RIV10-GA0-28140___
utb.identifier.obdid	43859485
utb.identifier.wok	000265636900027
utb.source	d-wok
dc.date.accessioned	2011-08-09T07:34:03Z
dc.date.available	2011-08-09T07:34:03Z
utb.contributor.internalauthor	Vařacha, Pavel
utb.fulltext.affiliation	PAVEL VARACHA Department Applied Informatics Tomas Bata University in Zlin Nad Stranemi 4511, Zlin, 760 05 CZECH REPUBLIC [email protected] http://www.fai.utb.cz
utb.fulltext.dates	-
utb.fulltext.references	[1] http://www.ue.cz/ [2] http://www.cez.cz/cs/uvod.html [3] BOSE, B.K., LIANG, P. 1996. Neural Network Fundamentals with Graphs, Algorithms, and Aplications. McGraw-Hill Series in Electrical and Computer Engineering, 478 p. ISBN 0-07 006618-3. [4] http://mathworld.wolfram.com/LevenbergMarquardtMethod.html [5] http://en.wikipedia.org/wiki/RMSD
utb.fulltext.sponsorship	This work was supported by National Program of Research II, project number 2C06007, of the Ministry of Education of the Czech Republic and by grant of the Grant Agency of the Czech Republic GACR 102/09/1680.
utb.fulltext.projects	2C06007
utb.fulltext.projects	GACR 102/09/1680