Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

<table>Membership functions for “<svg height="15.825" id="M28" style="vertical-align:-3.3907pt" version="1.1" viewbox="0 0 29.6625 15.825" width="29.6625" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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q2 -89 11 -177z" id="x54"></path></g>
<g transform="matrix(.012,-0,0,-.012,18.438,15.613)"><path d="M383 397q0 -32 -35 -49q-12 -6 -23 8q-37 45 -84 45t-90 -71q-40 -65 -40 -167q0 -57 22 -86t59 -29q38 0 81.5 24.5t69.5 51.5l16 -21q-44 -53 -104 -84t-109 -31q-56 0 -89.5 41t-33.5 117q0 61 30 124t79 105q33 28 81 50.5t86 22.5q34 0 59 -15.5t25 -35.5z" id="x1D450"></path></g><g transform="matrix(.012,-0,0,-.012,23.268,15.613)"><path d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" id="x31"></path></g>
</svg>” output variable.</table>

Advances in Artificial Intelligence

Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

Figure 4