## 5 Comparison between Predictive Analysis and Test Results  
### Compressive Strength  
Figure 15a,b shows the CLSM compressive strength analysis mode obtained by applying the compressive strength prediction analysis mode. Under the condition of the fixed water-binder ratio and different DS instead of a fine natural aggregate (the substitution amount is 0%, 10%, and 20% to 50%, respectively), the compressive strength and curing age of the CLSM are performed in a predictive analysis.  
This study uses Equation (10) to discuss the mean absolute percentage error (MAPE) ([PERSON] [28]). When the MAPE value is less than 10%, it means it has excellent predictive ability. When the MAPE value is between 10% and 20%, it means a good predictive ability; when the MAPE value is introduced between 20% and 50%, it means that it has a reasonable predictive capability; when the MAPE value is greater than 50%, it means that the predictive ability is incorrect. Considering the compressive strength of the curing age of one day, the MAPE value of the prediction result of the total compressive strength of different DS replacement amounts is 13.88%, as shown in Figure 16a. However, if the strength of the one-day compressive test specimen is excluded, the predicted model and the measured MAPE values are 9.17%, as shown in Figure 16b. The main reason for the large variation in the prediction results is that the variability of the compressive test specimen strength at the one-day age is higher than that of the test samples at other ages. However, the overall analysis results show that the predicted  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**w/b**} & \multirow{2}{*}{**DS**} & \multicolumn{2}{c}{**Coefficients of Hyperbolic Function**} \\ \cline{3-4}  & & \(a_{\sigma r}\) & \(b_{\sigma r}\) \\ \hline \multirow{4}{*}{1.5} & 0 & 0.4046 & 0.1070 \\  & 0.1 & 0.4516 & 0.1830 \\ \cline{1-1}  & 0.2 & 0.8950 & 0.0955 \\ \cline{1-1}  & 0.3 & 0.6342 & 0.1155 \\ \cline{1-1}  & 0.4 & 0.3581 & 0.1994 \\ \cline{1-1}  & 0.5 & 0.2990 & 0.2707 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Characteristics of the coefficients \(a_{\sigma r}\) and \(b_{\sigma r}\) of the relationship prediction model between the compressive strength and electrical resistivity versus the DS contents.  
Figure 14: The relationship of the compressive strength and surface resistivity with various DS contents.  
analytical values are quite close to the experimental results under the different DS replacements. Thus, the prediction model for the CLSM compressive strength proposed in this study can obtain good analytical results.  
\[MAPE=\frac{1}{k}\sum_{i=1}^{k}\left|\frac{y_{i}-\hat{y_{i}}}{y_{i}}\right| \tag{10}\]  
where \(y_{i}\) is a measurement, \(\hat{y_{i}}\) is the mode analysis value, and \(k\) is the number of analysis data.  
Figure 16: (**a**) Mean absolute percentage error (MAPE) value by applying the compressive strength prediction analysis (considering the results obtained by all curing ages). (**b**) MAPE value by applying the compressive strength prediction analysis (excluding the results obtained from the 1-day sample).  
Figure 15: (**a**) Comparison of the compressive strength between the predicted analysis and test results. (by curve graph) (**b**) Comparison of the compressive strength between the predicted analysis and test results. (by histogram)