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Krishak Sahayata: Prediction of Best Crop Yield

EasyChair Preprint no. 2413

4 pagesDate: January 18, 2020


Optimal crop yield forms the need for society to have people lead a healthy lifestyle for which various techniques and tools are employed which vary from predicting crop growth to identifying diseases using IoT, Machine Learning, Image Processing, etc. However, there is a need to develop a system to estimate the yield of crops which would be best suited for the specific set of climatic conditions. The focus of this paper is to provide a comparative study of the existing technologies and further propose Random Forest as one of the algorithms for enhancing the accuracy and efficiency of the yield production.

Keyphrases: Agriculture, machine learning, Yield Prediction

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Gresha Bhatia and Urjita Bedekar and Simran Bhagwandasani and Rahul Bhatia and Pranit Naik},
  title = {Krishak Sahayata: Prediction of Best Crop Yield},
  howpublished = {EasyChair Preprint no. 2413},

  year = {EasyChair, 2020}}
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