Akademik Veri Yönetim Sistemi
Selcuk Journal of Agriculture and Food Sciences, cilt.33, sa.3, ss.241-247, 2019 (Hakemli Dergi)
A 2-(5-8)-2 artificial neural network (ANN) model, with a back propagation learning algorithm, was developed to predict specific draft force and fuel con-sumption requirements of mouldboard plough in a clay loam soil under varying operating conditions. The input parameters of the network were tillage depth and forward speed of operation. The output from the network were the specific draft force and fuel consumption requirement of the mouldboard plough. The developed model predicted the specific draft force and fuel consumption re-quirement of mouldboard plough with an error <1 % when compared to the measured draft force and fuel consumption values. Such encouraging results indicate that the developed ANN model for specific draft force and fuel con-sumption requirement prediction could be considered as an alternative and practical tool for predicting draft force and fuel consumption requirement of tillage implements under the selected experimental conditions in clay loam soils. Further work is required to demonstrate the generalised value of this ANN in other soil conditions.