Application of Genetic Algorithm to Estimation of Function Parameters in Lightning Currents Approximations

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Parameter</td><td class="align_center">Value</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Population size</td><td class="align_center">100</td></tr><tr><td class="align_left">Number of generations</td><td class="align_center">150</td></tr><tr><td class="align_left">Number of elite individuals</td><td class="align_center">2</td></tr><tr><td class="align_left">Crossover fraction</td><td class="align_center">0.8, which equals 78 individuals</td></tr><tr><td class="align_left">Individuals created by mutation</td><td class="align_center">20</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Parameter settings for the genetic algorithm.

International Journal of Antennas and Propagation

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Table 1

Table 1: Application of Genetic Algorithm to Estimation of Function Parameters in Lightning Currents Approximations 