| Revista: | Maderas : ciencia y tecnología |
| Base de datos: | |
| Número de sistema: | 000544804 |
| ISSN: | 0718-221X |
| Autores: | Reis, Pamella Carolline Marques dos Reis1 Souza, Agostinho Lopes de1 Reis, Leonardo Pequeno2 Carvalho, Ana Márcia Macedo Ladeira1 Mazzei, Lucas3 Rêgo, Lyvia Julienne Sousa1 Leite, Helio Garcia1 |
| Instituciones: | 1Universidade Federal de Viçosa, Departamento de Engenharia Florestal, Viçosa, Minas Gerais. Brasil 2Instituto de Desenvolvimento Sustentável Mamirauá, Tefé, AM. Brasil 3Embrapa Amazônia Oriental, Belém, Pará. Brasil |
| Año: | 2018 |
| Periodo: | Jul |
| Volumen: | 20 |
| Número: | 3 |
| Paginación: | 343-352 |
| País: | Chile |
| Idioma: | Inglés |
| Resumen en inglés | 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. |
| Keyword: | Artificial intelligence, Modeling, Timber potential, Tropical wood, Wood technology |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
