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Modelling big data analysis approach with multi-agent system for crop-yield prediction

Author

Listed:
  • Jaya Sinha
  • Shri Kant
  • Megha Saini

Abstract

Big data environment in current scenario is dealing with challenges in handling inherent complexity residing in the massive heterogeneous, multivariate and continuously evolving real-time data along with offline statistics. The role of big data analytics to analyse such a highly diverse data also plays a significant role in estimating predictive performance of a system. This paper thus aims at proposing an intelligent agent-based architecture that coordinates with big data analytics framework to model a system with an objective to improve the predictive performance of system by handling such diverse data. The paper also includes implementing predictive algorithm to predict crop yield in the agricultural domain. Various machine learning analytical tools have been used for data analysis to produce comprehensive and more accurate prediction using the proposed architecture.

Suggested Citation

  • Jaya Sinha & Shri Kant & Megha Saini, 2023. "Modelling big data analysis approach with multi-agent system for crop-yield prediction," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 15(1), pages 27-45.
    • Handle: RePEc:ids:ijidsc:v:15:y:2023:i:1:p:27-45
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