Thumbnail Image

Chaudhary Charan Singh Haryana Agricultural University, Hisar

Chaudhary Charan Singh Haryana Agricultural University popularly known as HAU, is one of Asia's biggest agricultural universities, located at Hisar in the Indian state of Haryana. It is named after India's seventh Prime Minister, Chaudhary Charan Singh. It is a leader in agricultural research in India and contributed significantly to Green Revolution and White Revolution in India in the 1960s and 70s. It has a very large campus and has several research centres throughout the state. It won the Indian Council of Agricultural Research's Award for the Best Institute in 1997. HAU was initially a campus of Punjab Agricultural University, Ludhiana. After the formation of Haryana in 1966, it became an autonomous institution on February 2, 1970 through a Presidential Ordinance, later ratified as Haryana and Punjab Agricultural Universities Act, 1970, passed by the Lok Sabha on March 29, 1970. A. L. Fletcher, the first Vice-Chancellor of the university, was instrumental in its initial growth.

Browse

20141
Reset filters
Subject: Farm Machinery and Power Engineering × Author: Karwasra, Nitin × Start date: 2012 ×
Reset filters

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    ThesisItemOpen Access
    Application of artificial neural network in prediction of tractor performance
    (CCSHAU, 2014) Karwasra, Nitin; Anil Kumar
    Prediction of tractor performance can lead to simulation and optimization of tractor performance, allowing optimum setting of different parameters as well as enhancing decisionmaking of manufacturer in design of new tractor. In the present study was carried out to predict tractor drawbar and PTO performance. 20 input different parameters selected for both drawbar and PTO performance prediction. The data used as input to train the network is collected from 141 tractor test reports tested between 1997-2013 at Central Farm Machinery Training & Testing Institute, Budni (M.P.). A Back propagation artificial neural network was developed using Neural Network Toolbox in Matlab software. Matrix of 1140x20 and 1140x1 was made as input and target values for drawbar prediction and 1704x20 and 1704x1 for PTO prediction in ANN. The optimum structure of neural network was determined by a trial and error method and 30 different structures were tried. For prediction of tractor drawbar performance the highest performance was obtained for the network with two hidden layer each having 35 neurons which employed Levenberg-Marquardt training algorithm. Regression coefficient and mse for this model is 0.994 and 1.284 respectively. For prediction of tractor PTO performance ANN model with 2 hidden layers having 40 and 35 neurons in first and second layer respectively gives highest performance. Regression coefficient and mse for this model is 0.996 and 1.080. Both the models are now ready to predict the tractor performance based on 20 input parameters.