Determination of Drying Characteristics of Timber by Using Artificial Neural Networks and Mathematical Models

In this research, poplar and pine timbers have been dried in heat pump dryer functioning on the basis of 24-h operation. The change in weight in all of the timbers was followed in the drying chamber and drying stopped when the desired weight was achieved. Initial moisture content of the poplar timbers was 1.28 kg water/kg dry matter, and the moisture content was reduced to 0.15 kg water/kg dry matter moisture content in 70 h; the moisture content of the pine timbers, which was 0.60 kg water/kg dry matter, was reduced to the same amount in 50 h. Drying air temperature, relative humidity, and stack weight were measured and collected during drying and saved on a computer and analyzed afterwards. The moisture ratios were analyzed with Statgraphic computer program by using semitheoretical models and empirical values. Correlation and standard error of estimation (SEE) and R ² values were achieved.