Artificial neural networks to estimate the physical-mechanical properties of amazon second cutting cycle wood

Maderas: ciencia y tecnologia

Reis, Leonardo Pequeno¹  Souza, Agostinho Lopes de²  Reis, Pamella Carolline Marques dos Reis³ 

[1] Embrapa Amazônia Oriental, Belém, Brazil;Instituto de Desenvolvimento Sustentável Mamirauá, Tefé, Brasil;Universidade Federal de Viçosa, Viçosa, Brazil

关键词: Artificial intelligence;    modeling;    timber potential;    tropical wood;    wood technology.;   

DOI  :  10.4067/S0718-221X2018005003501

学科分类：农业科学（综合）

来源: Universidad del Bio-Bio

【 摘 要 】

Timber from the second cutting cycle may make up the majority of future crop volumetric. However, there are few studies of the physical and mechanical properties of this timber, which are important to support the consolidation of new species. This study aimed to use Artificial Neural Networks to estimate the physical and mechanical properties of wood from the Amazon, based on basic density. The properties were: shrinkage (tangential, radial and volumetric), static bending, parallel and perpendicular to the fiber compression, parallel and transverse to the fibers, Janka hardness, traction, splitting and shear. The estimate followed the tendency of the data observed for the tangential, radial and volumetric shrinkage. The network estimated the mechanical properties with significant accuracy. Distribution of errors, static bending, parallel compression and perpendicular to the fiber compression also showed significant accuracy. Artificial Neural Networks can be used to estimate the physical and mechanical properties of wood from Amazon species.

【 授权许可】

CC BY-NC