Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left"> </td><td class="align_center">TOLMIN</td><td class="align_center">NEWUOA</td><td class="align_center">BOBYQA</td><td class="align_center">LINCOA</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Hot case (°C)</td><td class="align_center">0.000</td><td class="align_center">0.000</td><td class="align_center">0.000</td><td class="align_center">0.000</td></tr><tr><td class="align_left">Cold case (°C)</td><td class="align_center">0.351</td><td class="align_center">0.000</td><td class="align_center">0.442</td><td class="align_center">0.351</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Error values achieved with Powell’s algorithms for steady-state cases (°C).

International Journal of Aerospace Engineering

tab3

Table 3

Table 3: Performance of Gradient-Based Solutions versus Genetic Algorithms in the Correlation of Thermal Mathematical Models of Spacecrafts 