Fuzzy Logic based Crop Yield Prediction using Temperature and Rainfall parameters predicted through ARMA, SARIMA, and ARMAX models

Agriculture plays a significant role in the economy of India. This makes crop yield prediction an important task to help boost India's growth. Crops are sensitive to various weather phenomena such as temperature and rainfall. Therefore, it becomes crucial to include these features when predicting the yield of a crop. Weather forecasting is a complicated process. In this work, three methods are used to forecast- ARMA (Auto Regressive Moving Average), SARIMA (Seasonal Auto Regressive Integrated Moving Average) and ARMAX (ARMA with exogenous variables). The performance of the three is compared and the best model is used to predict rainfall and temperature which are in turn used to predict the crop yield based on a fuzzy logic model.