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A machine learning-based approach for smart agriculture via stacking-based ensemble learning and feature selection methods
Smart irrigation has many advantages in optimizing resource usage (eg, saving water,
reducing energy consumption) and improving crop productivity. In this paper, we contribute …
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
Smart irrigation has many advantages in optimizing resource usage (eg, saving water,
reducing energy consumption) and improving crop productivity. In this paper, we contribute …
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
The study aims to determine the levels of soil parameters such as soil pH, macronutrients,
and micronutrients. After determining said parameters, the system appropriately …
and micronutrients. After determining said parameters, the system appropriately …
Computerized Irrigation Scheduling
Wasteful irrigation systems are significant contributors to water scarcity on the globe.
Irrigation Scheduling based on Machine Learning (ML) algorithms is considered essential in …
Irrigation Scheduling based on Machine Learning (ML) algorithms is considered essential in …
A Comparative Analysis of ML Algorithms to Improve Crop Productivity Prediction
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 …
2050. Additionally, water levels have been declining, and there is a shortage of usable …