Drvna industrija, Vol. 70 No. 3, 2019.
Original scientific paper
https://doi.org/10.5552/drvind.2019.1839
Application of Artificial Neural Network to Predict the Effect of Paraffin Addition on Water Absorption and Thickness Swelling of MDF
Ayşenur Gürgen
orcid.org/0000-0002-2263-7323
; Karadeniz Technical University, Faculty of Forestry, Forest Industrial Engineering, Trabzon, Turkey
Derya Ustaömer
; Karadeniz Technical University, Faculty of Forestry, Forest Industrial Engineering, Trabzon, Turkey
Sibel Yildiz
; Karadeniz Technical University, Faculty of Forestry, Forest Industrial Engineering, Trabzon, Turkey
Abstract
In this study, water absorption and thickness swelling values of medium density fiberboard (MDF) were modelled by artificial neural networks (ANN). MDF panels were produced with different rates of paraffin (0.0-control, 0.5, 1 and 1.5 %) at different press temperatures (170 and 190 °C). After conditioning of MDF, water absorption (WA) and thickness swelling (TS) of samples were carried out at specific intervals within 24 hours. Then, the data obtained from these experiment were modelled using ANN. Paraffin addition rate, press temperature and immersion time in water were used as the input parameters, while WA and TS values of MDF were used as the output parameters. After training of ANN, it was found that correlation coefficients (R) were close to 1 for training, validation, test and all data set. Mean absolute percentage error (MAPE) and mean square error (MSE) were determined as 2.94 % and 0.57, respectively, for all data sets. As a result of this study, the use of proposed ANN model may be recommended to predict the water absorption and thickness swelling of panels instead of complex and time-consuming studies such as empirical formulas.
Keywords
artificial neural network; water absorption; thickness swelling; medium density fiberboard; paraffin
Hrčak ID:
225630
URI
Publication date:
27.9.2019.
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