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Vol. 11, Special Issue 4 (2022)

Time series prediction for sugarcane production in Bihar using ARIMA & ANN model

Author(s):
Sudhir Paswan, Anupriya Paul, Ajit Paul and Ashish S Noel
Abstract:
Agriculture is important to the Indian economy and employment; India is the world's second-largest producer of sugarcane, which is a key cash crop in Bihar. The main objectives of this paper are to look into the stability and long-term viability of sugarcane production in the state of Bihar. For the study period 1939-40 to 2019-20, secondary data on sugarcane production was obtained from the Directorate of Economics and Statistics, Bihar and Sugarcane Industries Department, Bihar. Sugarcane production was predicted using the Box-Jenkins ARIMA model and artificial neural network (ANN) approach. To create the model and estimate the forecasting behaviour, the Box-Jenkins ARIMA Model was employed, as well as the ANN method. The ARIMA (1,1,0) model is the most suitable for forecasting based on the minimal value of AIC (649.781) and BIC (654.545). The model ARIMA (1,1,0) was presented for forecasting sugarcane production from 2020 to 2025, which indicated a significant increase from 126.03 lakh to 131.67 lakh ton. These forecast values are useful for collecting information and planning resources for the government, sugar mills, researchers, and businesspeople, as well as farmers making key decisions about sugarcane crop production in Bihar.
Pages: 1947-1956  |  438 Views  236 Downloads
How to cite this article:
Sudhir Paswan, Anupriya Paul, Ajit Paul and Ashish S Noel. Time series prediction for sugarcane production in Bihar using ARIMA & ANN model. The Pharma Innovation Journal. 2022; 11(4S): 1947-1956.

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