Proceedings Article10.1109/ICDT57929.2023.10151325
Crop recommendation using machine learning algorithms
P. Kumar,Kusum Lata,Sushant Jhingran +2 more
- 11 May 2023
pp 100-103
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TL;DR: In this article , the authors used machine learning algorithms such as random forest, Naive Bayes, KNN, decision tree, Logistic regression on which suggestions are made for growing a suitable crop.
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Abstract: A large part of the population of India considers agriculture to be their Main occupation. Crop production is important for our economy. Poor quality crop production is often caused by selecting the wrong crops on the wrong soil or having less knowledge of the different crop’s growth capabilities. The proposed system in which ML is used for crop recommendation is based on previously recorded measurements of soil parameters. This technique lessens the possibility of soil degradation and aids in crop health maintenance. Many factors which include rainfall. Temperature, pH, and N, P, K, humidity are analyzed using machine learning algorithms such as random forest, Naive Bayes, KNN, decision tree, Logistic regression on which suggestions are made for growing a suitable crop.
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Citations
Intelligent Crop Recommendation using Machine Learning
Santosh Kumar Upadhyay,Vikas +1 more
- 14 Mar 2024
TL;DR: This article provides a system for crop recommendations employing machine learning, especially the Random Forest algorithm (RF), and shows that the system is able to predict the best crop to grow with an accuracy of 99%.
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Crop Recommendation System Using ML Algorithms
Prof. Sonawane Meenakshi,Shaikh Moin,Dange Aniket,Salve Dnyaneshwari,Kaklij Rutuja +4 more
TL;DR: This paper reviews the crucial generalities, ways, challenges, and advancements related to ML algorithms employed in crop recommendation systems and discusses colourful datasets, evaluation criteria, and case studies available in the literature to illustrate the capabilities and limitations of being systems.
FASAL FUSION: An Approach to Transform Crop Recommendations
Manav Khandurie,Pratham Kandari,S. K. Tripathi,Tarun Mishra,Avita Katal +4 more
- 24 May 2024
TL;DR: A Crop Recommendation System is proposed to assist Indian farmers in choosing suitable crops based on soil factors, utilizing machine learning algorithms, achieving 99.24% accuracy with Random Forest Algorithm, to enhance agricultural productivity and resource utilization.
Machine Learning Based Hybrid System for Rainfall Prediction and Crop Recommendation
Yenumala Joseph Praveen,Deva Priya Isravel,Julia Punitha Malar Dhas,Gannamani Deepthi +3 more
- 16 May 2024
TL;DR: A novel system that incorporates Random Forest and Adaboost models is used to predict the rainfall and recommend crops and its effectiveness is evaluated using rigorous metrics like accuracy, precision, recall and prediction error metrics, ensuring reliable predictions and recommendations.
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Rakesh Kumar,Munindar P. Singh,Prabhat Kumar,Jyoti Prakash Singh +3 more
- 06 May 2015
TL;DR: Wang et al. as discussed by the authors proposed a method named Crop Selection Method (CSM) to solve crop selection problem, and maximize net yield rate of crop over season and subsequently achieves maximum economic growth of the country.
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Crop Yield Prediction Using Deep Reinforcement Learning Model for Sustainable Agrarian Applications
TL;DR: This work constructs a Deep Recurrent Q-Network model which is a Recurrent Neural Network deep learning algorithm over the Q-Learning reinforcement learning algorithm to forecast the crop yield, outperforming existing models by preserving the original data distribution.
Crop Yield Prediction using Machine Learning Techniques
Ramesh Medar,Vijay S. Rajpurohit,Shweta Shweta +2 more
- 29 Mar 2019
TL;DR: In this article, the authors implemented the crop selection method so that this method helps in solving many agriculture and farmers problems and improved the Indian economy by maximizing the yield rate of crop production.
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Crop Recommendation System using Machine Learning
Dhruvi Gosai,Chintal Upendra Raval,Rikin J Nayak,Hardik Jayswal,Axat Patel +4 more
- 01 Jun 2021
TL;DR: The proposed system of IoT and ML is enabled for soil testing using the sensors, is based on measuring and observing soil parameters, which lowers the probability of soil degradation and helps maintain crop health.
Machine Learning Based Crop Suggestion System
R. Varun Prakash,M. Mohamed Abrith,Sabarison Pandiyarajan +2 more
- 25 May 2022
TL;DR: This work collects temperature, humidity, soil moisture and pH values from the field and sends them through a Node MCU and data in the virtual storage (cloud) were analyzed using different machine learning algorithm such as SVM, Random forest, Naïve Bayes, XGBOOST and Decision trees.
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