Agricultural Economics and Practices
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The forecast values of rabi green gram production obtained from the fitted hybrid ARIMA-ANN model are found to be decreasing in future years, so it could be concluded that the advanced machine learning model definitely improves the accuracy of forecasting.
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Green gram is one of the major pulse crop of Odisha grown mostly during the Rabi seasons. Rabi green gram production accounts for approximately 51 percent of the total pulse production in Odisha. Data on production (in ‘000 MT) of rabi green gram are collected for the period from 1970-71 to 2023-2024. The entire data is splitted into two sets: training data set and testing/Cross validated data set. The data for the period from 1970-71 to 201920 for building training data set and 2020-21 to 2023-24 to be used as test data set/ cross validation data set. Classical Auto Regressive Integrated Moving Average (ARIMA) model and Artificial Neural Network (ANN) model is built for the training set data. Both the built-in models are compared on basis of Mean Absolute Percentage Error MAPE and Akaike Information Criteria Corrected (AICc) for the training set and test set data. The model performing better on basis of MAPE and AICc is selected for obtaining final forecast values of rabi green gram production.ARIMA (2, 0, 0) fits best which after performing the BDS test for the residuals shows that both linearity and non-linearity is found in the data in ratio of 7:1. So hybrid ARIMA-ANN model is prescribed to be fitted with appropriate weightage to selected best fit ARIMA and ANN models. Out of the suitable NNAR models, NNAR (2, 3) model to be the best fit. So the hybrid ARIMA-ANN model is fitted with weightage of 0.875 to the selected best fit ARIMA (2,0,0) model and 0.125 to the selected best fit NNAR (2,3) model. The model fit statistics for the hybrid ARIMA-ANN model is found to be lower in case of training data set and testing data set. The forecast values of rabi green gram production obtained from the fitted hybrid ARIMA-ANN model are found to be decreasing in future years. Thus, it could be concluded that the advanced machine learning model definitely improves the accuracy of forecasting.
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@article{Biswas2026Comparison,
title = {On Comparison of Classical and Machine Learning Models for Forecasting Rabi Green Gram Production in Odisha},
author = {Subhalaxmi Biswas and Abhiram Dash},
journal = {Journal of the Indian Society of Agricultural Statistics},
year = {2026},
doi = {10.56093/jisas.v80i2.6},
url = {https://doi.org/10.56093/jisas.v80i2.6}
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