Open Access   Article Go Back

Crop Suggesting System Using Unsupervised Machine Learning Algorithm

K.D. Yesugade1 , Hetanshi Chudasama2 , Aditi Kharde3 , Ketki Mirashi4 , Kajal Muley5

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 322-325, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.322325

Online published on Mar 31, 2019

Copyright © K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley, “Crop Suggesting System Using Unsupervised Machine Learning Algorithm,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.322-325, 2019.

MLA Style Citation: K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley "Crop Suggesting System Using Unsupervised Machine Learning Algorithm." International Journal of Computer Sciences and Engineering 7.3 (2019): 322-325.

APA Style Citation: K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley, (2019). Crop Suggesting System Using Unsupervised Machine Learning Algorithm. International Journal of Computer Sciences and Engineering, 7(3), 322-325.

BibTex Style Citation:
@article{Yesugade_2019,
author = {K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley},
title = {Crop Suggesting System Using Unsupervised Machine Learning Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {322-325},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3838},
doi = {https://doi.org/10.26438/ijcse/v7i3.322325}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.322325}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3838
TI - Crop Suggesting System Using Unsupervised Machine Learning Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - K.D. Yesugade, Hetanshi Chudasama, Aditi Kharde, Ketki Mirashi, Kajal Muley
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 322-325
IS - 3
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
503 356 downloads 179 downloads
  
  
           

Abstract

At this state of affairs several issues are faced by farmers in India, we have discovered that there is rise in suicide rate over the years. The reasons behind this includes weather conditions, debt, family issues and frequent change in Indian government norms. Sometimes farmers are not aware about the crop which suits their soil quality, soil nutrients and soil composition. Yield forecast is essential to agriculture stakeholders and can be obtained with the use of machine learning models and data coming from multiple sources.

Key-Words / Index Term

Climate, Sensors ,machine learning, agricultural productivity, crop production, prediction

References

[1] Nishit Jain, Amit Kumar, SahilGarud, Vishal Pradhan, PrajaktaKulkarni, “Crop Selection Method Based on Various Environmental Factors Using Machine Learning”,International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 02, Feb -2017.
[2] Igor Oliveira, Renato L. F. Cunha, Bruno Silva, Marco A. S. Netto, “A Scalable Machine Learning System for Pre-Season Agriculture Yield Forecast”,25 June 2018,14th IEEE eScience,https://arxiv.org/abs/1806.09244
[3] Rushika Ghadge, Juilee Kulkarni, Pooja More, Sachee Nene, Priya R L, “Prediction of crop yield using machine learning”, 2018 - International Research Journal of Engineering and Technology.
[4] S.Veenadhari, Dr. Bharat Misra, Dr.CD Singh, “Machine learning approach for forecasting crop yield based on climatic parameters”, International Conference on Computer Communication and Informatics (ICCCI -2014),Conference paper, Jan. 03 -05, 2014.
[5] Niketa Gandhi, LeisaJ.Armstrong, OwaizPetkar, Amiya Kumar Tripathi, “Rice crop yield prediction in India using SVM (Support Vector Machine).”, 2016 - 13th International Joint Conference on Computer Science and Software Engineering.
[6] Md. Tahmid Shakoor, Karishma Rahman, Sumaiya NasrinRayta, AmitabhaChakrabarty, “Agricultural Production Output Prediction Using Supervised Machine Learning Techniques”, IEEE, 2017.
[7] Prof.K.D.Yesugade, Sonal Bathiya, Priya Bora,Nikita Waykule,”Agro-sense:A Mobile App For Efficient Farming System Using Sensors”, International Research Journal of Engineering and Technology (IRJET), Volume: 04 Issue: 04,,April -2015.
[8] Rabina Dayal, Arun Kumar Yadav, “A Review of Different Techniques Utilized for Crop Yield Prediction”, International Journal Of Computer Science And Engineering, Vol.6, Issue.12, pp.437-442,2018