Optimization of Crop Recommendation System Using Machine Learning |
Author(s): |
| Prof. H.T. Gwalani , SIPNA College of Engineering and Technology, Amravati, India; Kartik Mone, SIPNA College of Engineering and Technology, Amravati, India; Anish Kene, SIPNA College of Engineering and Technology, Amravati, India; Mehardip Parkhe, SIPNA College of Engineering and Technology, Amravati, India; Dhanashri Ingale, SIPNA College of Engineering and Technology, Amravati, India |
Keywords: |
| Machine Learning, Crop Recommendation, Random Forest, Agriculture, Accurate Farming |
Abstract |
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Agricultural is one of the most essential areas for economic development, especially in developing countries. This paper presents a machine learning-based crop recommendation system that uses environment and soil parameters to recommend optimal crops for farmers. The model has been developed due to its accuracy and strength in handling its accuracy using the random forest algorithm. Major parameters such as soil pH, nitrogen, phosphorus, potassium, temperature, humidity, rainfall and soil type are used. The system acquired an accuracy of 98.2% and provided real -time recommendations through a web interface, assisting in clever and more sustainable farming decisions. |
Other Details |
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Paper ID: IJSRDV13I20114 Published in: Volume : 13, Issue : 2 Publication Date: 01/05/2025 Page(s): 152-157 |
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