Crop Yield Prediction using Deep Learning

Crop Yield Prediction using Deep Learning

B Madhan Sai

Artificial Intelligence and Machine learning Malla Reddy University

Hyderabad,India

2011cs020043@mallareddyuniversity.ac.in

B Phaninder

Artificial Intelligence and Machine learning Malla Reddy University

Hyderabad,India

2011cs020046@mallareddyuniversity.ac.in

B Nikhil

Artificial Intelligence and Machine learning Malla Reddy University

Hyderabad,India

2011cs020044@mallareddyuniversity.ac.in

K Vijaya

Artificial Inteligence and Machine Learning Malla Reddy University

Hyderabad,India

2011cs020045@mallareddyuniversity.ac.in

Prof.Thanish (Guide)
Artificial Intelligence and Machine learning
Malla Reddy University
Hyderabad,India

Abstract—Crop yield prediction plays a vital role in  agricultural planning, decision-making, and resource  allocation. Accurate forecasting of crop yields allows  farmers, policymakers, and stakeholders to optimize  production practices, manage risks, and ensure food  security. In recent years, deep learning techniques have  emerged as powerful tools for predictive modeling, offering  the potential to enhance crop yield prediction accuracy.

Keywords— Deep learning, Artificial neural networks,  Recurrent neural networks, Predictive Modeling, Resource  Allocation Agriculture Farming