Crop Recommendation System using ML

Notification

Announcement!

ISJEM Invites papers for various areas like engineering, Management, Science & other multi discplinary subjects. Please submit your paper for review.

ISJEM assigns a digital object identifier (DOI) to each published paper, making it easier for the paper to be cited in various major databases like Google Scholar, ResearchGate, Academia.edu, etc…

ISJEM takes 24–48 hours to publish a research paper. Within 24 hours, the submitted paper will be reviewed and notified of its status, and it will be published once the processing fee is successfully received.

Crop Recommendation System using ML

Version
Download 174
File Size 348.21 KB
File Count 1
Create Date 22 April 2023
Last Updated 22 April 2023

Crop Recommendation System using ML

Dr. D. Kavitha¹, R. Triveni², S. Harsha Vardhan³, N. Akhil⁴, V. Kumar ParasuRam⁵

Sr. Assistant Professor, Department of Information Technology¹

B.Tech Students, Department of Information Technology^2,3,4,5

Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

Abstract: The crop recommendation system using machine learning is an intelligent decision support system that provides recommendations to farmers on the most suitable crop to cultivate based on soil and weather conditions like temperature, humidity, rainfall, nitrogen, potassium, phosphorus and pH value of the soil. This system uses machine learning algorithms like Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to analyse data on soil properties, climate, and other relevant factors to generate personalized crop recommendations for each farmer.

Keywords: Crop Recommendation, temperature, humidity, rainfall, nitrogen, potassium, phosphorus, ph value, Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine (SVM), Logistic Regression, machine Learning.

Download