International Journal of Soft Computing

Year: 2017
Volume: 12
Issue: 2
Page No. 96 - 102

Prediction of Crop Yield Using Regression Techniques

Authors : Aditya Shastry, H.A. Sanjay and E. Bhanusree

References

Alan, O.S., 1993. An introduction to regression analysis. Master Thesis, University of Chicago Law School, Chicago, Illinois.

Asseng, S., G.C. Anderson, F.X. Dunin, I.R.P. Fillery and P.J. Dolling et al., 1997. Use of the APSIM wheat model to predict yield, drainage and NO3-leaching for a deep sand. Crop Pasture Sci., 49: 363-378.
Direct Link  |  

Carberry, P.S. and D.G. Abrecht, 1991. Tailoring Crop Models to the Semi-Arid Tropics. In: Climatic Risk in Crop Production: Models and Management in the Semi-Arid Tropics and Sub-Tropics, Muchow, R.C. and J.A. Bellamy (Eds.). Cab International, Wallingford, England, pp: 157-182.

Hearn, A.B., 1994. OZCOT: A simulation model for cotton crop management. Agric. Syst., 44: 257-299.
Direct Link  |  

Nancy, R.Z., 2010. Topic: Multiple Linear Regression. Stanford University, California,.

Qaddoum, K. and E.L. Hines, 2012. Reliable yield prediction with regression neural networks. Proceedings of the 12th WSEAS International Conference on Signal Processing, Computational Geometry and Artificial Intelligence, August 21-23, 2012, WSEAS Press, Turkey, Istanbul,-pp: 1.

Sanchez, A.G., J.F. Solis and W.O. Bustamante, 2014. Attribute selection impact on linear and nonlinear regression models for crop yield prediction. Sci. World J., 2014: 1-10.
Direct Link  |  

Zaefizadeh, M., A. Jalili, M. Khayatnezhad, R. Gholamin and T. Mokhtari, 2011. Comparison of Multiple Linear Regressions (MLR) and Artificial Neural Network (ANN) in predicting the yield using its components in the hulless barley. Adv. Environ. Biol., 10: 109-114.
Direct Link  |  

Zaw, W.T. and T.T. Naing, 2009. Modeling of rainfall prediction over Myanmar using polynomial regression. Proceedings of the International Conference on Computer Engineering and Technology, January 22-24, 2009, IEEE, New York, USA., ISBN:978-0-7695-3521-0, pp: 316-320.

Zhang, L., L. Lei and D. Yan, 2010. Comparison of two regression models for predicting crop yield. Proceedings of the IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), July 25-30, 2010, IEEE, New York, USA., ISBN:978-1-4244-9565-8, pp: 1521-1524.

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