Yield Prediction using Machine Learning for Agriculture Insurance

Abstract

India has achieved self dependency in food grain production by using modern technologies and better scientific approaches for cultivation. Beside this framers are less dependent on monsoon due to better irrigation facilities. Indian government provides various subsidies on seed, electricity and other agricultural equipment's to increase the income of the farmers. Indian government started various insurance schemes like PMFBY (PRADHAN MANTRI FASAL BIMA YOJANA) so that in spite of these efforts if due to some natural calamities like flood, drought or hail rain etc. farmers suffers losses then agriculture insurance is acting as a helping hand to manage the risk in yield loss to the farmers. We can say agriculture insurance is a risk management tool where the crop production risk is bear by government at a minimal cost. Millions of farmer’s are getting benefited by this schemes still agriculture insurance has not reached to maximum number of the farmers due to lack of awareness. The paper proposed a scientific approach using machine learning to calculate the loss to the farmers. So that they can be benefited at the most. The accuracy of the model comes out be 91%.