Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/cin/volume-2015/369298/figures/369298.fig.008a.svgz" name="369298.fig.008a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Evolution of fitness function (average)</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/cin/volume-2015/369298/figures/369298.fig.008b.svgz" name="369298.fig.008b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Accuracy of the ANN (average)</td></tr></table>

<div>Average results for ten classification problems using NMPSO algorithm. (a) Average error evolution. (b) Average weighted recognition rate.</div>

Computational Intelligence and Neuroscience

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Figure 8

Figure 8: Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms 