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Calibration for Wastewater Treatment Modeling: Hybrid Approaches Combining Fuzzy Logic, Reinforcement Learning, and Particle Swarm Optimization

dc.contributor.authorZhang, Yang
dc.contributor.authorLiu, Jipeng
dc.contributor.authorNiu, Qinwang
dc.contributor.authorWang, Xiaojian
dc.contributor.authorYang, Kun
dc.date.accessioned2026-08-20T11:56:15Z
dc.date.available2026-08-20T11:56:15Z
dc.date.copyright2026/02/23
dc.date.issued2026
dc.identifier.otherJOEEDU.EEENG-8427.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312869
dc.description.abstractAbstractIn this paper, novel calibration approaches are proposed for modeling wastewater treatment processes. The benchmark simulation model has been widely adopted to represent the integrated activated sludge and sedimentation processes. However, this ...
dc.publisherAmerican Society of Civil Engineers
dc.titleCalibration for Wastewater Treatment Modeling: Hybrid Approaches Combining Fuzzy Logic, Reinforcement Learning, and Particle Swarm Optimization
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue5
dc.journal.titleJournal of Environmental Engineering
dc.identifier.doi10.1061/JOEEDU.EEENG-8427
dc.journal.fristpage04026012-1
dc.journal.lastpage04026012-12
dc.page12
dc.treeJournal of Environmental Engineering:;2026:;Volume ( 152 ):;issue: 005
dc.contenttypeFulltext


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