Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks

Sáez, Doris; Sanz Bobi, Miguel Ángel; Cipriano, Aldo

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Campo DC	Valor	Lengua/Idioma
dc.contributor.author	Sáez, Doris	es-ES
dc.contributor.author	Sanz Bobi, Miguel Ángel	es-ES
dc.contributor.author	Cipriano, Aldo	es-ES
dc.date.accessioned	2025-09-26T18:24:50Z	-
dc.date.available	2025-09-26T18:24:50Z	-
dc.date.issued	1998-05-09	es_ES
dc.identifier.uri	http://hdl.handle.net/11531/105475	-
dc.description	Capítulos en libros	es_ES
dc.description.abstract		es-ES
dc.description.abstract	Describes a systematic methodology based on artificial neural networks for model identification and its application to the prediction of water chemical properties under normal operation conditions in a power plant. The model obtained allows detection of incipient anomalies by comparison between the real and predicted values.	en-GB
dc.format.mimetype	application/pdf	es_ES
dc.language.iso	en-GB	es_ES
dc.publisher	Sin editorial (Anchorage, Estados Unidos de América)	es_ES
dc.rights		es_ES
dc.rights.uri		es_ES
dc.source	Libro: IEEE International Joint Conference on Neural Networks - IJCNN 1998, Página inicial: 1-6, Página final:	es_ES
dc.subject.other	Instituto de Investigación Tecnológica (IIT)	es_ES
dc.title	Prediction of water chemical properties in the cycle of a coal power plant using artificial neural networks	es_ES
dc.type	info:eu-repo/semantics/bookPart	es_ES
dc.description.version	info:eu-repo/semantics/publishedVersion	es_ES
dc.rights.accessRights	info:eu-repo/semantics/restrictedAccess	es_ES
dc.keywords		es-ES
dc.keywords	Water , Chemicals , Power generation , Input variables , Predictive models , Power system modeling , Neural networks , Artificial neural networks , Fault detection , Equations	en-GB
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