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  Published Paper Details:

  Paper Title

CROP YIELD PREDICTION USING MACHINE LEARNING ALGORITHMS

  Authors

  Dr Murali G,  Bakka Hari Charan Reddy,  Bharath V S,  Dhanush S R,  Dilip S

  Keywords

Crop Yield Prediction

  Abstract


India is an Agriculture based economy whose most of the GDP comes from agriculture and its allied sectors which accounts for 20% of total GDP. The motivation of this project comes from the increasing suicide rates in farmers which may be due to low yield in crops. Climate and other environmental changes have become a major threat in the agricultural field. Machine learning is an essential approach for achieving practical and effective solutions for this problem. Predicting yield of the crop from historical available data like weather, soil, rainfall parameters and historic crop yield. We aim to achieve this using the machine learning algorithm. We did a comparative study of various machine learning algorithms, i.e., ANN, K Nearest Neighbor, Random Forest, SVM and Linear Regression. In this project a mobile application will be developed which predicts the crop yield in general and also for a particular crop. Along with that, it will suggest to the user which crop to grow in that particular season.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2205693

  Paper ID - 220200

  Page Number(s) - g25-g29

  Pubished in - Volume 10 | Issue 5 | May 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Dr Murali G,  Bakka Hari Charan Reddy,  Bharath V S,  Dhanush S R,  Dilip S,   "CROP YIELD PREDICTION USING MACHINE LEARNING ALGORITHMS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 5, pp.g25-g29, May 2022, Available at :http://www.ijcrt.org/papers/IJCRT2205693.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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