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dc.contributor.authorMinchala Avila, Luis Ismael
dc.contributor.authorSanchez, C
dc.contributor.authorYungaicela, M
dc.date.accessioned2018-01-11T16:47:36Z-
dc.date.available2018-01-11T16:47:36Z-
dc.date.issued2016-04-18
dc.identifier.isbn9781467395182
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84979279823&doi=10.1109%2fSYSCON.2016.7490538&partnerID=40&md5=f53a51d7025bdeb048c214c70c991b0a
dc.identifier.urihttp://dspace.ucuenca.edu.ec/handle/123456789/29168-
dc.description.abstractThis paper presents the methodology of design of three different modeling techniques for predicting cement quality using input-output measurements of the closed circuit grinding in a cement plant. The modeling approaches used are: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan. An OPC (OLE for process control) network configuration in the SCADA system allows online validations of the proposed models in order to select the best approach for real-time prediction of cement quality.
dc.language.isoen_US
dc.publisherINSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC.
dc.source10th Annual International Systems Conference, SysCon 2016 - Proceedings
dc.subjectAdaptive Neuro-Fuzzy Inference System
dc.subjectArtificial Neural Networks
dc.subjectBlack-Box Model
dc.subjectFineness Of The Cement
dc.titleA comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding
dc.typeArticle
dc.description.cityOrlando Florida
dc.ucuenca.idautor0301453486
dc.identifier.doi10.1109/SYSCON.2016.7490538
dc.ucuenca.embargoend2022-01-01 0:00
dc.ucuenca.afiliacionminchala-avila, l.i., universidad de cuenca, dep. electrical and electronic eng., av. 12 de abril, cuenca, ecuador
dc.ucuenca.afiliacionsanchez, c., universidad de cuenca, dep. electrical and electronic eng., av. 12 de abril, cuenca, ecuador
dc.ucuenca.afiliacionyungaicela, m., universidad de cuenca, dep. electrical and electronic eng., av. 12 de abril, cuenca, ecuador
dc.ucuenca.indicebibliograficoSCOPUS
dc.ucuenca.nombrerevista10th Annual International Systems Conference SysCon 2016
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