FORECASTING OF THE BROWN PLANT HOPPER DAMAGE IN RICE AT TELANGANA STATE – A STATISTICAL APPROACH
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Authors
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K.SUPRIYA* and G.C. MISHRA
Division of Agricultural Statistics, Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi - 221 005
Abstract
Research was conducted to forecast the damage due to Brown Plant Hopper in Rice in Telangana state
using the forecasting techniques Artificial Neural Network model (ANN), Autoregressive Integrated moving Average
model (ARIMA) and Autoregressive Integrated Moving Average model with exogenous variables (ARIMAX) and also
to compare their prediction accuracies. To forecast the damage pertaining to the BPH, data pertaining to the
damage caused by BPH was collected for 27 years during both kharif and rabi seasons of the Telangana state i.e.,
during 1990-2016. The results showed that artificial neural network (ANN) performed reasonably well compared to
the other models i.e., autoregressive integrated moving average model (ARIMA) and ARIMAX model and hence, can
be applied for real life predictions and modeling problems.
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