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Crop Yield Forecasting Using Artificial Neural Networks: A Comparison between Spatial and Temporal Models

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  • William W. Guo
  • Heru Xue

Abstract

Our recent study using historic data of wheat yield and associated plantation area, rainfall, and temperature has shown that incorporating statistics and artificial neural networks can produce highly satisfactory forecasting of wheat yield. However, no comparison has been made between the outcomes from the spatial neural network model and commonly used temporal neural network models in crop forecasting. This paper presents the latest research outcomes from using both the spatial and temporal neural network models in crop forecasting. Our simulation shows that the spatial NN model is able to predict the wheat yield with respect to a given plantation area with a high accuracy compared with the temporal NARNN and NARXNN models. However, the high accuracy of the spatial NN model in crop yield forecasting is limited to the forecasting of crop yield only within normal ranges. Users must be cautious when using either NARNN or NARXNN for crop yield forecasting due to their inconsistency between the results of training and forecasting.

Suggested Citation

  • William W. Guo & Heru Xue, 2014. "Crop Yield Forecasting Using Artificial Neural Networks: A Comparison between Spatial and Temporal Models," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, January.
    • Handle: RePEc:hin:jnlmpe:857865
    DOI: 10.1155/2014/857865
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    Cited by:

    1. Ansari Saleh Ahmar & Pawan Kumar Singh & R. Ruliana & Alok Kumar Pandey & Stuti Gupta, 2023. "Comparison of ARIMA, SutteARIMA, and Holt-Winters, and NNAR Models to Predict Food Grain in India," Forecasting, MDPI, vol. 5(1), pages 1-15, January.
    2. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
    3. Prabhjit Kaur & Kulvir Singh Saini & Sandeep Sharma & Jashanjot Kaur & Rajan Bhatt & Saud Alamri & Alanoud T. Alfagham & Sadam Hussain, 2023. "Increasing the Efficiency of the Rice–Wheat Cropping System through Integrated Nutrient Management," Sustainability, MDPI, vol. 15(17), pages 1-18, August.

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