UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 9 | September 2025

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Published in:

Volume 9 Issue 8
August-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2208348


Registration ID:
501423

Page Number

d412-d413

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Title

Comparative Study of Rice Crop Yield Prediction Techniques using ML

Abstract

Food is the most important thing for any living entity in the world. Human beings eat varieties of food across the world. One of the most popular food is rice. There are thousands of varieties of rice and that many number of ways to eat it. We have analyzed the ways in which rice crop can be yielded. In this paper we are comparing the various techniques used for rice crop yield prediction using machine learning so that rice production is more.

Key Words

rice crop yield prediction

Cite This Article

"Comparative Study of Rice Crop Yield Prediction Techniques using ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.d412-d413, August-2022, Available :http://www.jetir.org/papers/JETIR2208348.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Comparative Study of Rice Crop Yield Prediction Techniques using ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppd412-d413, August-2022, Available at : http://www.jetir.org/papers/JETIR2208348.pdf

Publication Details

Published Paper ID: JETIR2208348
Registration ID: 501423
Published In: Volume 9 | Issue 8 | Year August-2022
DOI (Digital Object Identifier):
Page No: d412-d413
Country: Pune, Maharashtra, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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