Clustering of Crops for Determining the Seasonal Crop Insurance using Machine Learning Techniques

Abstract

Weather Based Crop Insurance scheme depends on various factors such as Climate, Yield, Area coverage and humidity as recorded at a local weather station. In India the climate variability will make further impact on crop yield and insurance. It is possible to help the government agencies to insure the farmers by recommending the data mining techniques based on climatic factors of crop. This paper focusses on the application of clustering using k-means algorithm to cluster the crops to be insured based on adverse weather conditions such as Excess and deficit rainfall that prevails in the agriculture blocks of Coimbatore district.