Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

<table>The percentage of satisfied users (<svg height="15.4" id="M122" style="vertical-align:-3.3907pt" version="1.1" viewbox="0 0 17.9625 15.4" width="17.9625" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<g transform="matrix(.012,-0,0,-.012,10.875,15.187)"><path d="M515 96q-37 -44 -84.5 -76t-71.5 -32q-12 0 -18 7t-6 34t10 75l19 89h-2q-87 -113 -181 -176q-43 -29 -83 -29q-46 0 -46 63q0 31 9 67l52 222q7 36 -1 36q-10 0 -76 -50l-13 24q47 45 92 71.5t67 26.5q18 0 21 -16.5t-8 -65.5l-56 -242q-16 -67 13 -67q41 0 114 74
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</svg>) in the proposed algorithm against the three
references algorithms.</table>

Advances in Artificial Intelligence

Access Network Selection Based on Fuzzy Logic and Genetic Algorithms

Figure 7