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
India is an agrarian usa in which most people is engaged in agriculture. But deciding on the wrong crop results in decrease yields and excessive meals shortages. Thus, crop failure and environmental pollution have come to be a extreme trouble. And all this appointment moreover leads to spoil the various farmers. To overcome this scenario, we suggest a model with the intention to help predict the maximum suitable crop on a web page via reading weather and soil parameters. Naive Bayes, K-Nearest Neighbors, Decision Tree are some of algorithms that are in comparison in this article. Based on this evaluation, it's far viable to decide which of the techniques provides the greatest accuracy. The enter parameters of the meteorological tool can be statistics and first-rate parameters.
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Cite Article:
"CROP RECOMMENDATION FROM SOIL NUTRITION AND WEATHER DATA CURRENT LOCATION", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.310 - 314, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304060.pdf
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Publication Details:
Published Paper ID: IJSDR2304060
Registration ID:205030
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 310 - 314
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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