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Wood Science and Technology

Erschienen in:

01.10.2006 | ORIGINAL

Wood dielectric loss factor prediction with artificial neural networks

verfasst von: Stavros Avramidis, Lazaros Iliadis, Shawn D. Mansfield

Erschienen in: Wood Science and Technology | Ausgabe 7/2006

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Abstract

An artificial neural network that can predict the dielectric properties of wood was developed and tested with experimental data. The network was capable of accurately predicting the loss factor of two wood species not only as a function of ambient electro-thermal conditions but also as a function of basic wood chemistry. This way, an important predictive tool is created that allows optimization of dielectric heating and drying for many wood species without significant experimentation should their chemical composition be known under variable temperatures, moisture contents and electric filed characteristics.

Vorheriger Artikel Determination of formic-acid and acetic acid concentrations formed during hydrothermal treatment of birch wood and its relation to colour, strength and hardness

Nächster Artikel Characterization of Brauns’ lignin from fresh and vacuum-dried birch (Betula pendula) wood

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Titel: Wood dielectric loss factor prediction with artificial neural networks
verfasst von: Stavros Avramidis
Lazaros Iliadis
Shawn D. Mansfield
Publikationsdatum: 01.10.2006
Verlag: Springer-Verlag
Erschienen in: Wood Science and Technology / Ausgabe 7/2006
Print ISSN: 0043-7719
Elektronische ISSN: 1432-5225
DOI: https://doi.org/10.1007/s00226-006-0096-3

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