
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Crop Management Using Machine Learning Techniques
Author(s) | Shiva Kumar Chakali, Rishitha Erukulla, Harshitha Chinthareddy |
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Country | India |
Abstract | India is an agricultural nation where crop productivity plays a major role in the country's economy. Thus, it is possible to argue that agriculture will serve as the foundation for every business in our nation. The country's economy is growing mostly due to the agriculture sector. Changes in the climate and other environmental factors are becoming a serious danger to agriculture. The application of machine learning (ML) is a crucial strategy for finding workable and efficient answers to this issue. Crop yield prediction is the process of forecasting crop production using historical data, such as weather, soil, and previous crop output. This focuses on utilizing the Random Forest algorithm to forecast the crop's production based on the available data. The forecast will assist farmers in forecasting yield. |
Keywords | Random Forest, Machine learning, Crop yield, Historical data. |
Field | Engineering |
Published In | Volume 6, Issue 1, January-February 2024 |
Published On | 2024-01-09 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i01.11727 |
Short DOI | https://doi.org/gtdr6g |
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E-ISSN 2582-2160

CrossRef DOI is assigned to each research paper published in our journal.
IJFMR DOI prefix is
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