Improved GSO Optimized ESN Soft-Sensor Model of  Flotation Process Based on Multisource Heterogeneous Information Fusion

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="262368.fig.009a" src="https://static-preview.hindawi.com/articles/tswj/volume-2014/262368/figures/262368.fig.009a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Concentrate grade</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="262368.fig.009b" src="https://static-preview.hindawi.com/articles/tswj/volume-2014/262368/figures/262368.fig.009b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Flotation recovery rate</td></tr></table></td></tr></table>

<table>Predictive results of soft-sensor models (GA-ESN, PSO-ESN, and IGSO-ESN).</table>

The Scientific World Journal

fig9

Figure 9

Figure 9: Improved GSO Optimized ESN Soft-Sensor Model of  Flotation Process Based on Multisource Heterogeneous Information Fusion 