A COMPREHENSIVE SURVEY ON ESTIMATING CROP YIELDS BASED ON MACHINE LEARNING

Crop yield prediction is a critically important forecasting problem trying to address food security in the world. This is a crucial AI based application where the previous crop yield is used to train a machine learning model and then the future crop yield is forecasted. The results can be used to decide, which crop to be sown during a particular season in a particular geographical location. Since the data to be analyzed is large, random and complex for analysis, hence conventional statistical techniques do not render high accuracy of prediction. This paper presents a review on the contemporary techniques for crop yield prediction.The performance evaluation parameters have also been discussed.. It is expected that the paper would present with a headway for further research in cloud workload prediction.