Survival and Comparative study on Different Artificial Intelligence Techniques for Crop Yield Prediction

Saritha S; Abel Thangaraja G

doi:10.34256/ijcci2311

Saritha S Department of Computer Science, Shri Nehru MahaVidyalaya College of Arts and Science, Coimbatore-641050, Tamil Nadu, India.
Abel Thangaraja G Department of Computer Science, Shri Nehru MahaVidyalaya College of Arts and Science, Coimbatore-641050, Tamil Nadu, India.

Keywords: Agriculture, Economic Sector, Strategic Analysis, Crop Yield Prediction, Machine Learning

Abstract

Agriculture is an essential, important sector in the wide-reaching context. Farming helps to satisfy the basic need of food for every living being. Agriculture is considered the broadest economic sector. The crop yield is a significant part of food security and improves the drastic manner by human population. The quality and quantity of the yield touch the high rate of production. Farmers require timely advice to predict crop productivity. The strategic analysis also helps to increase crop production to meet the growing food demand. The forecasting of crop yield is a process of forecasting crop yield by using historical data. Machine learning provides a revolution in the agricultural field by changing the income scenario and growing an optimum crop. Many researchers carried out their research to deal with forecasting crop yield. In this way, accurate prediction of crop yield was improved. But, failed to reduce the crop yield prediction time and the accuracy level was not enhanced by existing methods.

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