Price forecasting system for crops at the sowing time
by Sanjeev Kumar; Shivashish Upadhyay; Sonal Singh; Saumya Sharma
International Journal of Agriculture Innovation, Technology and Globalisation (IJAITG), Vol. 2, No. 3, 2021

Abstract: There is a high volatile of price in the field of agriculture. We are trying to develop a price-forecasting model to predict the price of crops at the time of sowing. Prediction of price prior sowing the crop or before selling the crop is a key aspect of effective farm management. By using the past data and analysing its trend, we can predict the future trend and future price of the given crops. The past data regarding price of crops is tested for prediction purpose. Our developed model predicts the price of the crops before sowing seeds. Prediction of the price of crop is done by using auto regressive integrated moving average (ARIMA) model. We have used the rolling mean, standard deviation, Dickey-Fuller test, partial autocorrelation, function and auto-correlation function to verify the stationarity of the data. Further we have implemented auto regressive (AR) model, moving average (MA) model an auto regressive integrated moving average (ARIMA) model for the given time series data. Potato crop is used for forecasting purposes and the data is taken from a reliable government site. Our objective is to develop a price forecasting system that is helpful to maximise the profits of farmers.

Online publication date: Thu, 03-Mar-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Agriculture Innovation, Technology and Globalisation (IJAITG):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com