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Parallelisation of decision-making techniques in aquaculture enterprises

dc.contributor.authorIbáñez Bolado, Mario 
dc.contributor.authorLuna García, Manuel
dc.contributor.authorBosque Orero, José Luis 
dc.contributor.authorBeivide Palacio, Ramón 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2024-03-15T17:41:02Z
dc.date.available2024-03-15T17:41:02Z
dc.date.issued2023-07
dc.identifier.issn0920-8542
dc.identifier.issn1573-0484
dc.identifier.otherPID2019-105660RB-C22es_ES
dc.identifier.otherTED2021-131176B-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/32284
dc.description.abstractNowadays, the Artificial Intelligent (AI) techniques are applied in enterprise software to solve Big Data and Business Intelligence (BI) problems. But most AI techniques are computationally excessive, and they become unfeasible for common business use. Therefore, specific high performance computing is needed to reduce the response time and make these software applications viable on an industrial environment. The main objective of this paper is to demonstrate the improvement of an aquaculture BI tool based in AI techniques, using parallel programming. This tool, called AquiAID, was created by the research group of Economic Management for the Sustainable Development of Primary Sector of the Universidad de Cantabria. The parallelisation reduces the computation time up to 60 times, and the energy efficiency by 600 times with respect to the sequential program. With these improvements, the software will improve the fish farming management in aquaculture industry.es_ES
dc.description.sponsorshipThis work has been supported by the Spanish Science and Technology Commission under contracts PID2019-105660RB-C22 and TED2021-131176B-I00 and FPU21/03110.es_ES
dc.format.extent17 p.es_ES
dc.language.isoenges_ES
dc.publisherKluwer Academic Publisherses_ES
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceThe Journal of Supercomputing, 2023, 79(11), 11827-11843es_ES
dc.subject.otherAquaculturees_ES
dc.subject.otherParallelismes_ES
dc.subject.otherArtificial intelligencees_ES
dc.subject.otherDecision-makinges_ES
dc.subject.otherDistributed systemses_ES
dc.titleParallelisation of decision-making techniques in aquaculture enterpriseses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1007/s11227-023-05124-3es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105660RB-C22/ES/REDES DE INTERCONEXION, ACELERADORES HARDWARE Y OPTIMIZACION DE APLICACIONES/
dc.identifier.DOI10.1007/s11227-023-05124-3
dc.type.versionpublishedVersiones_ES


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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.Excepto si se señala otra cosa, la licencia del ítem se describe como This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material.