IJSDR
IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Analysis of soil and prediction of crop yield using machine learning approach
Authors Name: Saurabh Balaji Bhganagare , Aniket Babu Rathod , Komal Ramkrushna Wagh , Neha Sunil Kadam
Unique Id: IJSDR2211155
Published In: Volume 7 Issue 11, November-2022
Abstract: There are so many soil series available in India. Every soil series have different characteristics and every soil is suitable for different crop. Sometimes it happens that farmer soil is best for some specific crop but as he don’t know. The main goal of the given work is to create a suitable model for classifying various kinds of soil series data along with suitable crops suggestion. Series are recognized by machine learning methods using various chemical features and possible crops for that soil series are suggested using geographical attributes.
Keywords: Soil series, Land type, Chemical feature, Geographical attribute, machine learning, CNN, Regression
Cite Article: "Analysis of soil and prediction of crop yield using machine learning approach", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.1051 - 1053, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211155.pdf
Downloads: 000336257
Publication Details: Published Paper ID: IJSDR2211155
Registration ID:202703
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 1051 - 1053
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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