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

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="857865.fig.004a" src="https://static.hindawi.com/articles/mpe/volume-2014/857865/figures/857865.fig.004a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Original data</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="857865.fig.004b" src="https://static.hindawi.com/articles/mpe/volume-2014/857865/figures/857865.fig.004b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Cleaned data</td></tr></table></td></tr></table>

<table>Correlations between normalised wheat yield and plantation area.</table>

Mathematical Problems in Engineering

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Figure 4

Figure 4: Crop Yield Forecasting Using Artificial Neural Networks: A Comparison between Spatial and Temporal Models 