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 united states in which most of the people of the population is engaged in agriculture. But deciding on the incorrect crop leads to decrease yields and excessive forage shortages. Thus, crop failure and environmental pollution have become a extreme problem. And all this appointment, moreover, leads to the destroy of various farmers. To triumph over this scenario, we propose a model on the way to help expect the maximum suitable crop on a web web page by using reading weather and soil parameters. Naive Bayes, K-Nearest Neighbors, Decision Tree are a number of the algorithms which can be as compared in this newsletter. Based in this evaluation, you could determine which approach affords the maximum accuracy. The input parameters of the weather device may be statistical and number one 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.1822 - 1827, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304283.pdf
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000337070
Publication Details:
Published Paper ID: IJSDR2304283
Registration ID:205490
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 1822 - 1827
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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