Paper Title
Crop prediction using machine learning
Article Identifiers
Authors
Pragyna Parmar , Henvi Patel , akshita Patel , Hetvi Panchal
Keywords
crop, forcasting, temperature ,humidity, ph level.
Abstract
Abstract— India is mostly an agricultural country. Agriculture is essential to both the survival of humans and the Indian economy. Agriculture employs a sizable portion of the workforce as well. 70% of people living in rural India depend on agriculture for their livelihood. Crop output forecasting is one of the most difficult and soughtafter responsibilities that any government can carry out. Each farmer wants to know how much crop production they might expect in the near future. Large datasets may be mined for accuracy and previously unknown patterns or information using machine learning techniques. In this study, machine learning (ML) was used to select the optimum crop by considering a range of inputs, including temperature, humidity, pH level, etc
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How To Cite (APA)
Pragyna Parmar, Henvi Patel, akshita Patel, & Hetvi Panchal (March-2024). Crop prediction using machine learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), c652-c663. https://ijnrd.org/papers/IJNRD2403282.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : c652-c663
Other Publication Details
Paper Reg. ID: IJNRD_215654
Published Paper Id: IJNRD2403282
Downloads: 000121977
Research Area: Engineering
Country: Vadodara, Gujarat, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403282.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403282
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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