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A comparative study between mathematical models and the ANN data mining technique in draft force prediction of disk plow implement in clay loam soil CIGR Journal
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
Ano: 2018 URL:
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