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Mixture Optimization of Mechanical, Economical, and Environmental Objectives for a Novel Industrial Waste–Based Geopolymer: Combining Ensemble Learning with Metaheuristic Algorithms

dc.contributor.authorSu, Ruobin
dc.contributor.authorLin, Minguo
dc.contributor.authorChen, Geng
dc.contributor.authorChen, Yonghui
dc.contributor.authorHu, Nan
dc.contributor.authorWang, Junzhi
dc.contributor.authorYe, Zi
dc.date.accessioned2026-08-20T11:32:38Z
dc.date.available2026-08-20T11:32:38Z
dc.date.copyright2025/11/18
dc.date.issued2026
dc.identifier.otherJMCEE7.MTENG-20626.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312350
dc.description.abstractAbstractA novel industrial waste–based geopolymer prepared with silica fume–based activator is more effective and cost-efficient than traditional geopolymers, but is not widely used due to insufficient research on optimized mix proportions and ...
dc.publisherAmerican Society of Civil Engineers
dc.titleMixture Optimization of Mechanical, Economical, and Environmental Objectives for a Novel Industrial Waste–Based Geopolymer: Combining Ensemble Learning with Metaheuristic Algorithms
dc.typeJournal Article
dc.journal.volume38
dc.journal.issue2
dc.journal.titleJournal of Materials in Civil Engineering
dc.identifier.doi10.1061/JMCEE7.MTENG-20626
dc.journal.fristpage04025537-1
dc.journal.lastpage04025537-12
dc.page12
dc.treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 002
dc.contenttypeFulltext


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