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Artificial Neural Network Based Modeling of Tractor Performance at Different Field Conditions CIGR Journal
Almaliki, Salim; Alimardani, Reza; Omid, Mahmoud.
Application of tractors in farming is undeniable as a power supply. Therefore, performance model for evolving parameters of tractors and implements are essential for farm machinery, operators and manufacturers alike. The objective of this study was to assess the predictive capability of several configurations of ANNs for performance evaluating of tractor in parameters of drawbar power, fuel consumption, rolling resistance and tractive efficiency. A conventional tillage system which included a moldboard plow with three furrows was used for collecting data from MF285 Massey Ferguson tractor. To predict performance parameters, ANN models with back-propagation algorithm were developed using a MATLAB software with different topologies and training algorithms....
Tipo: Info:eu-repo/semantics/article Palavras-chave: Artificial neural network; Tractive efficiency; Rolling resistance; Drawbar power; Fuel consumption..
Ano: 2016 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3880
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