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A novel approach for forecasting algal bloom: long short-term memory artificial neural network with exponential smoothing feedback optimized by the arithmetic mean algorithm.

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第一作者： Hakan,Isık

第一单位： Department of Bioprocess Engineering, Institute of Science, Giresun University, 28200, Giresun, Türkiye. hakan.isik@giresun.edu.tr.;Department of Biology, Faculty of Arts and Science, Giresun University, 28200, Giresun, Türkiye. hakan.isik@giresun.edu.tr.

作者： Hakan,Isık ^[1] ; Erol,Egrioglu ^[2] ; Eren,Bas ^[2] ; Buse Eraslan,Akkan ^[3] ; Tamer,Akkan ^[4]

作者单位： Department of Bioprocess Engineering, Institute of Science, Giresun University, 28200, Giresun, Türkiye. hakan.isik@giresun.edu.tr.;Department of Biology, Faculty of Arts and Science, Giresun University, 28200, Giresun, Türkiye. hakan.isik@giresun.edu.tr. ^[1] Department of Data Science and Analytics, Faculty of Arts and Science, Giresun University, 28200, Giresun, Türkiye. ^[2] Natural Sciences Division, Mehmet Akif Ersoy Middle School, 28200, Giresun, Türkiye. ^[3] Department of Biology, Faculty of Arts and Science, Giresun University, 28200, Giresun, Türkiye. ^[4]

关键词 Arithmetic mean optimization algorithm Artificial neural networks Chlorophyll-a Exponential smoothing Forecasting Long short term memory

DOI 10.1038/s41598-026-57110-3

PMID 42277175

发布时间 2026-06-11

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