Crop Yield Forecasting Using Neural Networks

  • Mukesh Meena
  • Pramod Kumar Singh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8298)


The crop production forecasting has become an important issue, now, as it is a key factor for our economy and sustainable development on account of increased demand of the food grains with growing population. It helps farmers and government to develop a better post-harvest management at local / regional / national level, e.g., transportation, storage, distribution. Additionally, it helps farmers to plan next year’s crop and government to plan import/export strategies. This work is based on the yield forecasting of the pearl millet (bajra) in the Jaipur region of Rajasthan, India. The proposed method uses a back propagation artificial neural network to forecast current yield of the crop with respect to the environmental factors using time series data. The obtained results are encouraging and much better in comparison to a recent fuzzy time series based methods for forecasting.


Crop yield forecasting Pearl millet Time series Correlation analysis Neural network 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Mukesh Meena
    • 1
  • Pramod Kumar Singh
    • 1
  1. 1.Computational Intelligence and Data Mining Research LabABV-Indian Institute of Information Technology and Management GwaliorIndia

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