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dc.contributor.authorAliev, A.R.-
dc.contributor.authorGahramanli, Y.N.-
dc.contributor.authorAliyev, S.I.-
dc.date.accessioned2023-04-30T22:19:19Z-
dc.date.available2023-04-30T22:19:19Z-
dc.date.issued2022-06-
dc.identifier.issn2616-6127-
dc.identifier.issn2617-4383-
dc.identifier.otherhttps://doi.org/10.32010/26166127.2022.5.1.87.93-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/80-
dc.description.abstractThis paper described the opportunity to use artificial neural networks to predict the chemical reaction result under given conditions. Applied three layers neural network for prediction of the mass content of alkaline trained using the results of the chemical reactions. As inputs were used values of the chemical quantities before the reaction and output values of the chemical quantities after the reaction. HPC technologies and multi-worker technology were used for accurate results.en_US
dc.language.isoenen_US
dc.publisherAzerbaijan Journal of High Performance Computingen_US
dc.subjectData Predictionen_US
dc.subjectParallelizationen_US
dc.subjectNeural Networksen_US
dc.subjectMulti Worker Processingen_US
dc.titleRESEARCH ON THE VOLUME WEIGHT OF FOAMED COMPOSITES BASED ON BRICK WASTE USING NEURAL NETWORKSen_US
dc.typeArticleen_US
dc.source.journaltitleAzerbaijan Journal of High Performance Computingen_US
dc.source.volume5en_US
dc.source.issue1en_US
dc.source.beginpage87en_US
dc.source.endpage93en_US
dc.source.numberofpages7en_US
Appears in Collections:Azerbaijan Journal of High Performance Computing

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