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MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing
Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timberExpand
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Artificial Neural Networks in Wood Identification: The Case of two Juniperus Species from the Canary Islands
Neural networks are complex mathematical structures inspired on biological neural networks, capable of learning from examples (training group) and extrapolating knowledge to an unknown sampleExpand
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Abies pinsapo forests in Spain and Morocco: threats and conservation
Abstract The conifer forests of the Mediterranean Basin have been subjected to overuse by humans since ancient times. Some species have survived in inaccessible refuges but the ranges of otherExpand
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Adaptive anatomy of Pinushalepensis trees from different Mediterranean environments in Spain
A study was conducted on the variation in growth, biomass, juvenile wood anatomy, and needle morphology of Pinushalepensis Mill. from three Spanish regions of provenance characterized byExpand
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Characterisation of the xylem of 352 conifers
Siguiendo los metodos tradicionales de preparacion y descripcion de la madera a nivel microscopico, se han realizado 352 descripciones de maderas de coniferas. Para la caracterizacion de cada maderaExpand
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Reduction of wood hygroscopicity and associated dimensional response by repeated humidity cycles
La reduction de la reponse du bois aux variations d'humidite ambiante, decrite comme une forme de vieillissement, a ete etudiee du double point de vue de la reprise d'humidite et des variationsExpand
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Artificial neural networks in variable process control: application in particleboard manufacture
Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study twoExpand
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Comparison of modelling using regression techniques and an artificial neural network for obtaining the static modulus of elasticity of Pinus radiata D. Don. timber by ultrasound
Abstract The traditional regression method was compared with an artificial neural network for obtaining the static modulus of elasticity (MOEstatic) of Pinus radiata timber using the dynamic modulusExpand
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Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model
The physical properties (specific gravity, moisture content, thickness swelling and water absorption) and mechanical properties (internal bond strength, bending strength and modulus of elasticity)Expand
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Prediction of MOR and MOE of structural plywood board using an artificial neural network and comparison with a multivariate regression model
Abstract The structural application of plywood boards has increased considerably in recent years. In this context, determining plywood mechanical properties such as bending strength and modulus ofExpand
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