Agriculture Crop Selection and Yield Prediction using Machine Learning Algorithms
M Aruna Devi, Dhina Suresh, D. Jeyakumar, D Swamydoss, M. Lilly Florence
Abstract
Agriculture is the most fundamental and essential occupation for every human being. Without agriculture there is no living being, au are chained through web of life. In India agriculture is the main occupation, around 67% of people involving in agriculture. Inventors release many smart technologies in all the field like health sector, automobiles, education, etc. to improve our life styles and make our work easy. In the same way farmers also started to use smart technologies in the field of agriculture to improve the cultivation productivity. Recently the cities are transformed to smart cities through advanced technologies, similarly agriculture also turns slowly into technology enabled farming. Many farmers practicing green farming technologies to improve the production rate. In this regards, this paper proposes a model to select the appropriate crop for cultivation and predict the production rate using the weather parameters which are very much influencing the agriculture. Random Forest algorithm is the widely used machine learning algorithm for classification and prediction. The outcome of Random Forest is compared with Support Vector Machine algorithm The authors concluded that the proposed model works on average accuracy of 90%.