Implementation of Effective Crop Selection by Using the Random Forest Algorithm

  • Authors

    • R Karthikeyan
    • M Gowthami
    • A Abhishhek
    • P Karthikeyan
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.19209
  • Crop production, Machine learning, Random Forests, Weather Conditions

  • Abstract

    Accurate predictions of crop yield are critical for developing agriculture. We have provided a machine-learning method, Random Forests which has a ability to predict crop yield corresponds to the current climate and biophysical change. We have collected a large crop yield data from various sources. These data are used for both for the model training and testing.RF was found huge capable of predicting crop yields and over performed MLR standards in every performance statistics that were compared. From various results that shows that RF is an efficient machine-learning algorithm for crop predictions at current condition and has a huge accuracy in data analysis.

     

     

  • References

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  • How to Cite

    Karthikeyan, R., Gowthami, M., Abhishhek, A., & Karthikeyan, P. (2018). Implementation of Effective Crop Selection by Using the Random Forest Algorithm. International Journal of Engineering & Technology, 7(3.34), 287-290. https://doi.org/10.14419/ijet.v7i3.34.19209

    Received date: 2018-09-07

    Accepted date: 2018-09-07

    Published date: 2018-09-01