Design A Model for Crop Prediction And Analysis Using Machine Learning

Authors

  • Ruchira C. Mahore  MTech, Department of Computer Science Govt. College of Engineering, Amravati, India
  • Naresh G. Gadge  Assistant Professor, Department of Computer Science Govt. College of Engineering, Amravati, India

DOI:

https://doi.org/10.32628/CSEIT228681

Keywords:

Crop prediction, SVM, Machine learning

Abstract

Agriculture is the most important aspect of survival. Machine learning (ML) could be an important point of view in determining a practical and workable solution to the crop yield problem. Given the current method, which includes manual counting, climate-smart pest management, and satellite photography, the results aren't particularly accurate. The primary goal of this research is to forecast crop and yield yield using various machine learning approaches. SVM, Nave Bayes, and Random Forest are the classifier models used here, with Random Forest providing the highest accuracy. Machine learning algorithms will help farmers choose which crop to cultivate based on variables such as temperature, rainfall, area, and other characteristics This connects the technological and agricultural sectors .

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-01-30

Issue

Volume 9, Issue 1, January-February-2023

Section

Research Articles

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How to Cite

[1]
Ruchira C. Mahore, Naresh G. Gadge, " Design A Model for Crop Prediction And Analysis Using Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 1, pp.90-95, January-February-2023. Available at doi : https://doi.org/10.32628/CSEIT228681