Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Solid mining waste to cement ratio</td><td class="align_center">Fine sand ratio</td><td class="align_center">Solid mining waste to water ratio</td><td class="align_center">Curing time</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">4, 6, 8, and 10</td><td class="align_center">0, 0.1, 0.15, 0.2</td><td class="align_center">0.68, 0.70, 0.72</td><td class="align_center">7, 28, 60 days</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Advances in Civil Engineering

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Table 1

Table 1: Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models 

Table 1 | Estimating the Compressive Strength of Cement-Based Materials with Mining Waste Using Support Vector Machine, Decision Tree, and Random Forest Models 