A New Artificial Neural Network Model for the Prediction of the Effect of Molar Ratios on Compressive Strength of Fly Ash-Slag Geopolymer Mortar

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Material</td><td class="align_center" colspan="3">Chemical composition (wt%)</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left" rowspan="2">Na<sub>2</sub>SiO<sub>3</sub></td><td class="align_center">Na<sub>2</sub>O</td><td class="align_center">SiO<sub>2</sub></td><td class="align_center">Water</td></tr><tr><td class="align_center">14.7</td><td class="align_center">35</td><td class="align_center">50.3</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Composition of sodium silicate.</div>

Advances in Civil Engineering

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Table 2

Table 2: A New Artificial Neural Network Model for the Prediction of the Effect of Molar Ratios on Compressive Strength of Fly Ash-Slag Geopolymer Mortar 

Table 2 | A New Artificial Neural Network Model for the Prediction of the Effect of Molar Ratios on Compressive Strength of Fly Ash-Slag Geopolymer Mortar 