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dc.contributor.authorHernández López, Ángela
dc.contributor.authorCamacho Espino, Jorge
dc.contributor.authorPeñate Suárez, Baltasar
dc.contributor.authorMarichal Plasencia, Graciliano Nicolás
dc.date.accessioned2024-10-13T20:05:08Z
dc.date.available2024-10-13T20:05:08Z
dc.date.issued2023
dc.identifier.issn2076-3417
dc.identifier.urihttp://riull.ull.es/xmlui/handle/915/39561
dc.descriptionhttps://doi.org/10.3390/app13063392
dc.description.abstractThis work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) onboardamarinevessel. Thisinvestigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.ispartofseriesApplied Sciences, 13(6), 2023.
dc.rightsLicencia Creative Commons (Reconocimiento-No comercial-Sin obras derivadas 4.0 Internacional)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es_ES
dc.titleEnergy efficiency optimization in onboard SWRO desalination plants based on a genetic neuro-fuzzy systemen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3390/app13063392
dc.subject.keyworddesalinationen
dc.subject.keywordgenetic neuro-fuzzyen
dc.subject.keywordenergy efficiencyen
dc.subject.keywordintelligent controlen
dc.subject.keywordsoft computing techniquesen


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