Crop Recommendation System using Random Forest Algorithm in Machine Learning

The crop recommendation system employing machine learning methods will be covered in this study. For sustainable agricultural practices to be followed and to increase crop yields, crop advice is crucial. Based on several factors, including nitrogen (N), phosphorus (P), potassium (K), and humidity, w...

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Bibliographic Details
Published in:	2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) pp. 501 - 505
Main Authors:	Sani, Siva Ramakrishna, Sekhar Ummadi, Surya Venkata, Thota, SriRajarajeswari, Muthineni, Nikitha, Srinivas Swargam, Varun Sai, Ravella, Teja Sree
Format:	Conference Proceeding
Language:	English
Published:	IEEE 04-05-2023
Subjects:	Agriculture Crop Recommendation system Crops Decision Tree K-Nearest Neighbors Machine Learning Nitrogen Phosphorus Planning Prediction algorithms Predictive models Random Forest Support vector machines
Online Access:	Get full text
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Summary:	The crop recommendation system employing machine learning methods will be covered in this study. For sustainable agricultural practices to be followed and to increase crop yields, crop advice is crucial. Based on several factors, including nitrogen (N), phosphorus (P), potassium (K), and humidity, we will advise the best crop for the given site. We analyzed various algorithms like KNN, Decision Tree, Random Forest, SVM etc. But based on various accuracy levels we committed to random forest implementation. Means, In this paper we are going implement crop recommendation system using random forest algorithm. The model allowed to train upon large dataset and the performance of the recommendation system is measured using accuracy score. Finally, Using the trained model we are going to predict suitable crop for land according to the given parameters. Our proposed approach can be helpful for farmers, researchers, and policymakers in making informed decisions regarding crop managementand planning.
DOI:	10.1109/ICAAIC56838.2023.10141384