PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/cin/volume-2018/6094685/figures/6094685.fig.005a.svgz" name="6094685.fig.005a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Mean</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/cin/volume-2018/6094685/figures/6094685.fig.005b.svgz" name="6094685.fig.005b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Standard deviation</td></tr></table>

<div>The bar chart of Bonferroni-Dunn test for PS-FW and other PSO variants over mean and standard deviation of best solutions based on Table <a href="../tab10/">10</a>.</div>

Computational Intelligence and Neuroscience

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Figure 5

Figure 5: PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization 