Cost Optimization of Graphene Oxide-Modified Ultra-High-Performance Concrete Based on Machine Learning Methods

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datacite.relatedItem.firstPage181
datacite.relatedItem.issue7
datacite.relatedItem.relatedIdentifierTypeISSN
datacite.relatedItem.relatedItemIdentifier2304-6740
datacite.relatedItem.relationTypeIsPublishedIn
datacite.relatedItem.titleInorganics
datacite.relatedItem.volume12
dc.contributor.authorHui Lv
dc.contributor.authorMingfeng Du
dc.contributor.authorZijian Li
dc.contributor.authorLi Xiao
dc.contributor.authorShuai Zhou
dc.date.accessioned2024-08-15T13:41:28Z
dc.date.available2024-08-15T13:41:28Z
dc.date.issued2024
dc.identifier.doihttps://doi.org/10.3390/inorganics12070181
dc.identifier.otherjz000077-0072
dc.identifier.urihttps://tustorage.ulb.tu-darmstadt.de/handle/tustorage/6178
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddc540
dc.titleCost Optimization of Graphene Oxide-Modified Ultra-High-Performance Concrete Based on Machine Learning Methods
dc.typeArticle
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