Real-Time Evaluation of Compaction Quality by Using Artificial Neural Networks

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left" rowspan="3">HMA surface layers</td><td class="align_center">4 cm SMA-13</td></tr><tr><td class="align_center">6 cm AC-20</td></tr><tr><td class="align_center">8 cm AC-25</td></tr><tr><td class="align_left">Flexible base layer</td><td class="align_center">12 cm LSPM-25</td></tr><tr><td class="align_left">Semirigid base layer</td><td class="align_center">2 × 18 cm cement-stabilized aggregate</td></tr><tr><td class="align_left">Sub-base layer</td><td class="align_center">18 cm cement-stabilized weathered sands</td></tr><tr><td class="align_left">Subgrade</td><td class="align_center">Compacted natural soil</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Pavement structure in the project.</div>

Advances in Materials Science and Engineering

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Table 1

Table 1: Real-Time Evaluation of Compaction Quality by Using Artificial Neural Networks 