Implementation of Adaptive Neuro-fuzzy Model to Optimize Operational Process of Multiconfiguration Gas-Turbines

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/ahep/volume-2020/6590138/figures/6590138.fig.0012a.svgz" name="6590138.fig.0012a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Specific fuel consumption (SFC)</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/ahep/volume-2020/6590138/figures/6590138.fig.0012b.svgz" name="6590138.fig.0012b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Power output</td></tr><tr class="fig-image" id="c"><td><object data="https://static.hindawi.com/articles/ahep/volume-2020/6590138/figures/6590138.fig.0012c.svgz" name="6590138.fig.0012c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Thermal efficiency</td></tr></table>

<div>The comparison between the real and predicted data using the ANFIS model.</div>

Advances in High Energy Physics

fig12

Figure 12

Figure 12: Implementation of Adaptive Neuro-fuzzy Model to Optimize Operational Process of Multiconfiguration Gas-Turbines 