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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 113
Article Submitted : 18245
Article Published : 7789
Total Authors : 20583
Total Reviewer : 750
Total Countries : 142
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| Paper Title: | Precision Crop Care Recommender System Using Machine Learning Techniques. |
| Authors Name: | Pratham Kapratwar , Dr. T. Praveen Blessington , Ishwar Mahajan , Pallavi Dandge , Trupti Ghogare |
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IJRTI_185443
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| Published Paper Id: | IJRTI2303011 |
| Published In: | Volume 8 Issue 3, March-2023 |
| DOI: | |
| Abstract: | Agriculture is India's main source of employment and revenue. Choosing the incorrect crop for their land and using the incorrect fertilizer are the two biggest problems Indian farmers face. Their output will thus considerably decrease. With the help of the Precision Crop Care Recommender System, the farmer’s problem has been solved. The Precision Crop Care Recommender System is a modern farming method that suggests the best crop to farmers as well as fertiliser suggestions based on site-specific attributes using research data on soil properties, soil types, and crop production statistics. This increases output and decreases the frequency of incorrect crop selection. A recommendation system using ML models and a majority vote technique is developed in order to accurately and effectively recommend a crop for the site-specific factors. It employs Logistic Regression, Support Vector Machine (SVM), Random Forest, and Decision Tree. Python logic serves as the only foundation for the fertiliser recommendation system. After classifying the most variable nutrient t as HIGH or LOW, recommendations are then retrieved in line with the findings. |
| Keywords: | Agriculture, Recommendation system, Random Forest, Support Vector Machine (SVM), Logistic Regression. |
| Cite Article: | "Precision Crop Care Recommender System Using Machine Learning Techniques.", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 3, page no.61 - 64, March-2023, Available :http://www.ijrti.org/papers/IJRTI2303011.pdf |
| Downloads: | 000205136 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2303011
Registration ID:185443
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 61 - 64 Country: Pune, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2303011 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2303011 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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