Fuzzy Logic-Based Paddy Yield Prediction to Facilitate Weather Index-Based Crop Insurance

Abstract

Weather risk can be considered as the dominant among the risks associated with agriculture. The unpredictability of weather and its adverse impact on agriculture has made the industry unstable. However, the authorities have not been able to provide farmers with a mechanism which assures that their livelihood is preserved. To address this issue, Weather index-based crop insurance has been used in many countries. Risk modeling is an important component in this insurance. After quantifying the uncertainties in crop harvest due to weather factors, the insurance company can guide the farmers accordingly. Crop yield prediction based on weather factors can be used for this. This study proposes a Fuzzy Logic System which relates input (weather factors) and output (crop yield) variables through linguistic rules. The output of this model can be used for risk modeling in weather index-based crop insurance based on which the possible paddy crop damage can be minimized.