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

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dc.contributor.authorSáez Hueichapan, Doris Andrea
dc.contributor.authorSanz-Bobi, M. A.
dc.contributor.authorCipriano, Aldo
dc.date.accessioned2022-05-17T15:57:21Z
dc.date.available2022-05-17T15:57:21Z
dc.date.issued1998
dc.description.abstractDescribes 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.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/IJCNN.1998.687163
dc.identifier.isbn780348591
dc.identifier.issn1098-7576
dc.identifier.urihttps://doi.org/10.1109/IJCNN.1998.687163
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=687163
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64075
dc.information.autorucEscuela de Ingeniería ; Sáez Hueichapan, Doris Andrea ; S/I ; 1502
dc.information.autorucEscuela de Ingeniería ; Cipriano Zamorano, Aldo ; S/I ; 99102
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherIEEE
dc.relation.ispartofIEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (1998 : Anchorage, AK, Estados Unidos)
dc.rightsacceso restringido
dc.subjectWater
dc.subjectChemicals
dc.subjectPower generation
dc.subjectInput variables
dc.subjectPredictive models
dc.subjectPower system modeling
dc.subjectNeural networks
dc.subjectArtificial neural networks
dc.subjectFault detection
dc.subjectEquations
dc.titlePrediction of water chemical properties in the cycle of a coal power plant using artificial neural networkses_ES
dc.typecomunicación de congreso
sipa.codpersvinculados1502
sipa.codpersvinculados99102
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