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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 12, DECEMBER 2023

CLOUD COMPUTING USING MACHINE LEARNING FOR AGRICULTURE APPLICATION

Dr. Vikrant Sharma, Dr. Jayanthiladevi

DOI: 10.17148/IJARCCE.2023.121221

Abstract: Three types of machine learning were used in this paper: support vector machines (SVM), random forests, and the Naive Bayes. There are four main categorization metrics used to assess the efficiency of the system designed for the identification of insect pests. The four metrics covered here are accuracy, precision, recall, and F1-score. These results demonstrate that our enhanced SVM provides superior performance to the state-of-the-art approaches for automatic pest identification in crops.

Keywords: Machine Learning, Random Forests, SVM, Naive Bayes Cite: Dr. Vikrant Sharma, Dr. Jayanthiladevi,"CLOUD COMPUTING USING MACHINE LEARNING FOR AGRICULTURE APPLICATION", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 12, no. 12, pp. 132-138, 2023, Crossref https://doi.org/10.17148/IJARCCE.2023.121221.

How to Cite:

[1] Dr. Vikrant Sharma, Dr. Jayanthiladevi, “CLOUD COMPUTING USING MACHINE LEARNING FOR AGRICULTURE APPLICATION,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.121221