CROP YIELD PREDICTION USING MACHINE LEARNING

CROP YIELD PREDICTION USING MACHINE LEARNING

Joseph Pushparaj

Assistant Professor . Department of Computer Science and Engineering

PSN College of Engineering and Technology, Tirunelvei, Tamil Nadu, India

Ponnu Lakshmi

UG Student. Department of Computer Science and Engineering

PSN College of Engineering and Technology, Tirunelvei, Tamil Nadu, India

Abstract-India is an Agriculture based economy whose most of the GDP comes from farming. The motivation of this project comes from the increasing suicide rates in farmers which may be due to low harvest in crops. Climate and other environmental changes have become a major threat in the agriculture field. Machine learning is an essential approach for achieving practical and effective solutions for this problem. Predicting yield of the crop from historical available data like weather, soil, rainfall parameters and historic crop yield. We achieved this using the machine learning algorithm. We did a comparative study of various machine learning algorithms, i.e., ANN, K Nearest Neighbour, Random Forest, SVM and Linear Regression and chose Random Forest Algorithm which gave an accuracy of 95%. In this project a web application has been developed which predicts the crop yield in general and also for a particular crop. Along with that, it also suggests the user if it is the right time to use the fertilizer or not.

Index Terms- ANN, SVM, Random Forest