Publicación:
Machine Learning Weather Soft-Sensor for Advanced Control ofWastewater Treatment Plants

dc.contributor.authorHernández del Olmo, Félix
dc.contributor.authorGaudioso Vázquez, Elena
dc.contributor.authorDuro Carralero, Natividad
dc.contributor.authorDormido Canto, Raquel
dc.date.accessioned2024-05-20T11:42:52Z
dc.date.available2024-05-20T11:42:52Z
dc.date.issued2019
dc.description.abstractControl of wastewater treatment plants (WWTPs) is challenging not only because of their high nonlinearity but also because of important external perturbations. One the most relevant of these perturbations is weather. In fact, different weather conditions imply different inflow rates and substance (e.g., N-ammonia, which is among the most important) concentrations. Therefore, weather has traditionally been an important signal that operators take into account to tune WWTP control systems. This signal cannot be directly measured with traditional physical sensors. Nevertheless, machine learning-based soft-sensors can be used to predict non-observable measures by means of available data. In this paper, we present novel research about a new soft-sensor that predicts the current weather signal. This weather prediction differs from traditional weather forecasting since this soft-sensor predicts the weather conditions as an operator does when controling the WWTP. This prediction uses a model based on past WWTP influent states measured by only a few physical and widely applied sensors. The results are encouraging, as we obtained a good accuracy level for a relevant and very useful signal when applied to advanced WWTP control systems.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.3390/s19143139
dc.identifier.issn1424-8220
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12456
dc.journal.issue14
dc.journal.titleSensors
dc.journal.volume19
dc.language.isoen
dc.publisherMDPI
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentInteligencia Artificial
dc.rightsAtribución 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subject.keywordswastewater treatment plants
dc.subject.keywordssoft-sensors
dc.subject.keywordsmachine learning techniques
dc.titleMachine Learning Weather Soft-Sensor for Advanced Control ofWastewater Treatment Plantses
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery7c2613b6-1a06-4187-9cd1-4c51f5016c51
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