An experimental and theoretical examination of pine woods dried in the vacuum dryer by artificial neural network

The drying characteristics of the pine woods were examined in the vacuum drying system under different operating conditions. Three drying temperatures insert ignore into journalissuearticles values(40, 50 and 60 ◦C);, three operating pressures insert ignore into journalissuearticles values(0.6, 0.7 and 0.8 bar); and three times of exposure to vacuum insert ignore into journalissuearticles values(5, 10 and 15 minutes); were investigated. Experiments were carried out to obtain data from the sample moisture content. In this study, the application of Artificial Neural Network insert ignore into journalissuearticles values(ANN); to estimate pine woods` moisture content insert ignore into journalissuearticles values(output parameters for ANN modeling); was examined. Drying time, drying temperature, relative humidity, pressure and air temperature were accepted as the input parameters of the model. Training and validation were performed with great accuracy. The moisture content of woods is formulated by the ANN method. The proposed method offers more flexibility; therefore, the determination of the moisture content in pine woods is quite simpler.