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Precision Agriculture: Machine Learning-Driven Crop Yield Prediction in India

  • Unique Paper ID: 167795
  • Volume: 11
  • Issue: 4
  • PageNo: 1177-1183
  • Abstract:
  • Precise crop yield prediction has become very important in enhancing agricultural productivity and securing food systems. This project seeks to apply machine learning regression algorithms for crop yield prediction using variables such as weather conditions, soil properties, and historical yield data, including Linear Regression, Decision Trees, Random Forest. With advanced data analytics and machine learning techniques at play, this project should aid farmers and other agricultural stakeholders in coming up with reliable yield forecasts that present them with the ability to make informed decisions on resource allocation. In that case, this methodology features data collection and pre-processing of relevant agricul- tural data, selecting and implementing appropriate regression algorithms, and training and validation using historical crop yield data to assess the accuracy and predictive robustness. Attention is paid to feature engineering and model parameter optimization to bring out the best performance in making predictions. An accurate predictive model is, therefore, expected to contribute towards improving agricultural planning and sustainability.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 4
  • PageNo: 1177-1183

Precision Agriculture: Machine Learning-Driven Crop Yield Prediction in India

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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