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| Shafaei, Seyed Mojtaba; Loghavi, Mohammad; Kamgar, Saadat. |
| This paper communicates the prediction of required draft force of disk plow implement during tillage operations. The well-known mathematical model proposed by American Society of Agricultural and Biological Engineers (ASABE), multiple linear regression (MLR) and data mining model, based on artificial neural network (ANN), were employed for this purpose. The input variables of the models were considered as forward speed of 2-6 (km/h) and plowing depth of 10-30 (cm). The development details of the models are documented in the paper. On account of statistical performance criteria, the best ANN model with coefficient of determination of 0.971, root mean square error of 0.762 (kN), mean absolute percentage error of 1.886 (%) and mean value of absolute... |
| Tipo: Info:eu-repo/semantics/article |
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| Ano: 2018 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4466 |
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| Shafaei, Seyed Mojtaba; Loghavi, Mohammad; Kamgar, Saadat. |
| This work was dedicated to describe overall energy efficiency of machinery in plowing process as affected by some operational variables of plowing depth (10-30 cm) and forward speed (2-6 km/h). To achieve this aim, field trials in clay loam soil in southern region of Iran were performed by means of disk plow implement and front wheel assist tractor. The effects of the operational variables on the efficiency were examined. General two-variable linear and quadratic equations were fitted to obtained field data in order to model the efficiency with respect to plowing depth and forward speed. The results demonstrated that the individual effect of plowing depth on the efficiency was more dominant (1.2 times) than that of forward speed. Meanwhile, the compounded... |
| Tipo: Info:eu-repo/semantics/article |
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| Ano: 2023 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7603 |
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