Energy Sources, Part A: Recovery, Utilization and Environmental Effects, vol.38, no.8, pp.1075-1080, 2016 (SCI-Expanded)
Article / Article
Energy Sources, Part A: Recovery, Utilization and Environmental Effects
Science Citation Index Expanded (SCI-EXPANDED), Scopus
Drying, drying rate, neuro-fuzzy, oak, pine, poplar, timber, ARTIFICIAL NEURAL-NETWORKS, FLUIDIZED-BED DRYER, PREDICTION
Anadolu University Affiliated:
© 2016 Taylor & Francis Group, LLC.In this study, the drying rate of poplar, pine, and oak timbers is estimated using an adaptive neuro-fuzzy inference system (ANFIS). Experimental data were used for training and testing networks. The R2 value obtained when unknown data were applied to the networks was 0.99982 for the drying rate of poplar timbers, 0.999028 for the drying rate of pine timbers, and 0.999968 for the drying rate of oak timbers, which is very satisfactory. The method proposed offers more flexibility and therefore drying analysis of different timber kinds is fairly simplified.