Análises Bibliométricas Sobre a Produção E Tecnologia De Celulose E Papel De Eucalipto

Moura, Geiciane da Mota; Campos, Annanda Souza de; Silva, Daniela Szuta da; Lienard, Rafael Barbosa Diógenes; Freitas, Maria Cintia Silva de; Moura, Jenifer Nathanna Marcelino de; Trazzi, Paulo André

doi:10.55592/cfb.2022.5287494

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2023

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“…Segundo o levantamento bibliométrico [Campos et al 2022], o Brasil lidera o número de estudos voltados à produc ¸ão e tecnologia de papel de eucalipto. Desses estudos, grande parte deles buscam melhorar as estimativas da produc ¸ão afim de atender as demandas desses subprodutos, com modelos mais robustos associados a variáveis tanto do inventário, quanto fora dele.…”

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Modeling of growth and production of Eucalyptus spp stands using supervised machine learning

Araujo,

Soares,

Silva

et al. 2023

Anais Do XX Encontro Nacional De Inteligência Artificial E Computacional (ENIAC 2023)

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The forest sector is one of the most important pillars of the Brazilian economy due to its high wood productivity. Several studies are being carried out seeking to develop a computational method capable of estimating production efficiently in order to reduce production costs. The objective of the study was to develop machine learning models capable of estimating present and future eucalyptus production with high precision, evaluating relevant supervised learning models, like neural networks and support vector machine (SVM), in relation to the Clutter model, widely adopted by the forestry industries. A case study conducted on real data obtained from a continuous forest inventory showed that SVM is efficient to estimate growth and production of eucalyptus.

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