Forecasting rice production in Indonesia using regression techniques: A comparative analysis of support vector machine, linear regression, and XGBoost regression

E Yoshino, FI Kurniadi, B Juarto - 2023 10th International …, 2023‏ - ieeexplore.ieee.org
Population growth is straining the agricultural sector, posing a significant threat to global
food security. In Indonesia, rice is a staple diet, with annual demand growth of 1.16 percent …

[PDF][PDF] Advancements in Machine Learning and Deep Learning Techniques for Crop Yield Prediction: A Comprehensive Review.

V Ramesh, P Kumaresan - Nature Environment & Pollution …, 2024‏ - researchgate.net
Agriculture is the crucial pillar and basic building block of our nation. Agriculture plays a key
role as the major source of revenue for our nation. Farming is the primary financial source of …

Zone-II & III: Machine Learning based Rice Yield Prediction in Andhra Pradesh

S Ramisetty, D Bansode, VK Atmakur… - MATEC Web of …, 2024‏ - matec-conferences.org
In a unique approach, this research predicts rice yield in Zones II and III of Andhra Pradesh
using machine learning algorithms. Because food security and agricultural sustainability are …