Aug 16, 2023 · A crop production model proposed in aims to manage the produced crop using machine learning algorithms to help farmers in developing countries who are still using …

Mar 1, 2025 · Using machine learning (ML) for crop yield prediction can be challenging, particularly in selecting appropriate algorithms. Despite significant research, the growing …

Accurate crop prediction is essential to maximize yield and optimize resource usage, ensuring food security and economic stability. This paper presents an advanced model that integrates …

In the Crop Recommendation module, users can provide soil data, state, and city information, and the application employs a machine learning model to predict the optimal crops based on …

Methods: In this study, we address the critical issue of crop prediction by leveraging advanced machine-learning techniques and integrating genetic algorithms into the predictive model.

Aug 18, 2023 · Fifteen different algorithms have been considered to evaluate the most appropriate algorithms to use in agriculture, and a new feature combination scheme-enhanced …

May 22, 2023 · The authors suggested a prediction method using the following supervised machine-learning algorithms; Random Forest (RF), Support Vector Machine (SVM), Decision …

Sep 13, 2024 · These methods include regression models, ensemble methods, deep learning models, and support vector machines. MAE, RMSE, R 2 , precision, and recall are just a few …

Methods: This article proposes hybrid ML algorithms that use specialized ensembling methods such as stacked generalization, gradient boosting, random forest, and least absolute …

Oct 1, 2020 · Several machine learning algorithms have been applied to support crop yield prediction research. In this study, we performed a Systematic Literature Review (SLR) to …