Development of Artificial Neural-Network-Based Models for the Simulation of Spring Discharge

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="686258.fig.003a" src="https://static.hindawi.com/articles/aai/volume-2011/686258/figures/686258.fig.003a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Training</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="686258.fig.003b" src="https://static.hindawi.com/articles/aai/volume-2011/686258/figures/686258.fig.003b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Testing</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="686258.fig.003c" src="https://static.hindawi.com/articles/aai/volume-2011/686258/figures/686258.fig.003c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>Validation</td></tr></table></td></tr></table>

<table>Observed and predicted (ANN2) weekly spring discharge—quick-propagation algorithm.</table>

Advances in Artificial Intelligence

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Figure 3

Figure 3: Development of Artificial Neural-Network-Based Models for the Simulation of Spring Discharge 