Authors :
Karuppasamy K. M; K. Senthamarai Kannan
Volume/Issue :
Volume 8 - 2023, Issue 9 - September
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/ytxb7fkh
DOI :
https://doi.org/10.5281/zenodo.8376502
Abstract :
Time series analysis is one of the utmost
popular forecasting techniques in predicting the
upcoming events based on preceding performance. In this
paper, monthly regular prices of Rice data were used in
seasonal auto regressive integrated moving average
(SARIMA), simple exponential smoothing model and
naïve method incorporated to predict the upcoming
prices of Rice and thereby compared. SARIMA and
simple exponential smoothing model was found
appropriate for all Indian rice price. The performance
evaluation of the fitted model was observed by calculating
various measures. The SARIMA model was the most
typical model at the cost estimation of paddy in by and
large India. Those models were best fitted for predicting
of Rice Price in India. Prediction was made for the
immediate next two years that is 01-06-2021 to 01-05-
2023. The performance evaluation of these models were
validated by comparison with percentage deviation from
the actual values and mean absolute error (MAPE),
which was found to be 4.18% for the price under rice in
India.
Keywords :
SARIMA, Simple Exponential Smoothing, Naïve Model, AIC, BIC and Forecasting.
Time series analysis is one of the utmost
popular forecasting techniques in predicting the
upcoming events based on preceding performance. In this
paper, monthly regular prices of Rice data were used in
seasonal auto regressive integrated moving average
(SARIMA), simple exponential smoothing model and
naïve method incorporated to predict the upcoming
prices of Rice and thereby compared. SARIMA and
simple exponential smoothing model was found
appropriate for all Indian rice price. The performance
evaluation of the fitted model was observed by calculating
various measures. The SARIMA model was the most
typical model at the cost estimation of paddy in by and
large India. Those models were best fitted for predicting
of Rice Price in India. Prediction was made for the
immediate next two years that is 01-06-2021 to 01-05-
2023. The performance evaluation of these models were
validated by comparison with percentage deviation from
the actual values and mean absolute error (MAPE),
which was found to be 4.18% for the price under rice in
India.
Keywords :
SARIMA, Simple Exponential Smoothing, Naïve Model, AIC, BIC and Forecasting.
