The purpose of this study was to use Autoregressive Integrated Moving Average, Exponential smoothing, and the Neural Network (NN) model to produce a better forecast for yield of early maturing pigeonpea planted in India's central zone. The constructed model's performance was evaluated using various selection measure criteria, with the model with the lowest value of these criteria being designated the best forecasting model. In comparison to two other models, the neural network was found to be more suitable for predicting pigeonpea yield.
Author(S) Details
Prity Kumari
Section of Agricultural Statistics, Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, India.
G. C. Mishra
Section of Agricultural Statistics, Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi-221005, India.
C. P. Srivastava
Department of Entomology and Agricultural Zoology Institute of Agricultural Sciences, Banaras Hindu University Varanasi-221005, India.
View Book:- https://stm.bookpi.org/CTAS-V5/article/view/6268
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