POD DAMAGE MODELING AND FORECASTING IN EARLY MATURING PIGEONPEA ( TURING PIGEONPEA (Cajanus cajan) Cajanus cajan) FOR CENTRAL ZONE (CZ) FOR CENTRAL ZONE (CZ) OF INDIA
Keywords:
percent pod damage by, Pod borer, Neural network, Exponential smoothing, model, AutoregressiveAbstract
The present investigation was aimed to compare the ability of Autoregressive Integrated Moving Average (ARIMA), Exponential smoothing and Neural network (NN) model for forecasting percent pod damage by pod borer in early maturing pigeonpea yield grown in central zone of India. Based on studies, neural network was found to be more suitable for predicting pigeonpea yield as compared to two other models.
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Published
2018-05-11
How to Cite
PRITY KUMARI AND G. C. MISHRA. (2018). POD DAMAGE MODELING AND FORECASTING IN EARLY MATURING PIGEONPEA ( TURING PIGEONPEA (Cajanus cajan) Cajanus cajan) FOR CENTRAL ZONE (CZ) FOR CENTRAL ZONE (CZ) OF INDIA. The Bioscan, 13(2), 643–646. Retrieved from https://thebioscan.com/index.php/pub/article/view/2223
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