Agriculture Crop Analysis System using SVM Algorithm

Abstract

The cultivating division in India is confronting extreme difficulties in boosting crop efficiency. Still 60 percent of the crop is subject to precipitation. Late advancements in data innovation for the cultivating part have become an intriguing exploration region for evaluating crop yields. The issue of salary determining is a major issue that remaining parts to be tackled dependent on the accessible information. Information mining strategies are a best decision for this reason. Different information mining strategies are utilized and assessed in farm to gauge future crop yields. This venture presents a short examination of crop yield gauges utilizing SVM calculations. In today's life, farming is not done like our ancestors. Many factors, such as global warming, make it difficult to understand climatic conditions. So the farmers could not understand which crop would improve the production on the farm. Understanding soil and month types conditions using this data mining system will enable farmers to get the right crop at the right time which will improve the yield. The farmer asks farm related questions of the consultant and consultants provide solutions to the farmer. This project will help to solve these agriculture problems using SVM algorithms.