A machine learning-based approach for smart agriculture via stacking-based ensemble learning and feature selection methods

EB Abdallah, R Grati, K Boukadi - 2022 18th International …, 2022‏ - ieeexplore.ieee.org
Smart irrigation has many advantages in optimizing resource usage (eg, saving water,
reducing energy consumption) and improving crop productivity. In this paper, we contribute …

A machine learning approach for a robust irrigation prediction via regression and feature selection

EB Abdallah, R Grati, M Fredj, K Boukadi - International Conference on …, 2022‏ - Springer
Smart irrigation has many advantages in optimizing resource usage (eg, saving water,
reducing energy consumption) and improving crop productivity. In this paper, we contribute …

[PDF][PDF] Machine learning for the detection of soil pH, macronutrients, and micronutrients with crop and fertilizer recommendations

JJ Montañez, J Sarmiento - Int J Artif Intell, 2025‏ - researchgate.net
The study aims to determine the levels of soil parameters such as soil pH, macronutrients,
and micronutrients. After determining said parameters, the system appropriately …

Computerized Irrigation Scheduling

BAT Koné, R Grati, B Bouaziz… - 2023 20th ACS/IEEE …, 2023‏ - ieeexplore.ieee.org
Wasteful irrigation systems are significant contributors to water scarcity on the globe.
Irrigation Scheduling based on Machine Learning (ML) algorithms is considered essential in …

A Comparative Analysis of ML Algorithms to Improve Crop Productivity Prediction

A Nigam, D Jain, MS Talan, SK Singh… - 2023 International …, 2023‏ - ieeexplore.ieee.org
According to numerous calculations, the global food output must significantly increase by
2050. Additionally, water levels have been declining, and there is a shortage of usable …