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	Provedor de dados CIGR Journal (2) Autor Alimardani, Reza (1) Almaliki, Salim (1) Farhadi, Payam (1) Golmohammadi, Abdollah (1) Omid, Mahmoud (1) Shahgholi, Gholamhossein (1) Sharifi Malvajerdi, Ahmad (1) Mais... Palavra-chave Rolling resistance (2) Artificial Neural Network (ANN) (1) Artificial neural network (1) Contact area (1) Contact volume (1) Drawbar power (1) Fuel consumption. (1) Three-dimensional footprint (1) Tractive efficiency (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2019 (1) 2016 (1) País China (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última 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 Prediction of the tractor tire contact area, contact volume and rolling resistance using regression model and artificial neural network CIGR Journal Farhadi, Payam; Golmohammadi, Abdollah; Sharifi Malvajerdi, Ahmad; Shahgholi, Gholamhossein. A novel method to estimate the contact area and contact volume was developed with molding the tire footprint by liquid plaster and converting these molds to three-dimensional models using a 3D scanner. A 12.4-28, 6 ply tractor tire was operated under three levels of vertical load, three levels of inflation pressure and three levels of soil moisture content. To analyses the obtained data regression and Artificial Neural Network (ANN) models were used and the accuracy of predicted results were compared with measured data. A multi-layer perceptron feed-forward ANN with back propagation (BP) learning algorithm was employed. Two hidden layers were used in network architecture and the best number of neuron for each hidden layer was selected with attention to... Tipo: Info:eu-repo/semantics/article Palavras-chave: Artificial Neural Network (ANN); Contact area; Contact volume; Rolling resistance; Three-dimensional footprint. Ano: 2019 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5438 Registros recuperados: 2 Primeira ... 1 ... Última

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