# Prediction of Unconfined Compressive Strength in Cement-Treated Soils: A Machine Learning Approach
## 3 Results and Discussion
### Experimental Test Results
#### 3.1.2 Initial Assessment of Key Factors Affecting UCS  
To comprehensively assess the dominant factors governing UCS development, correlation analysis was performed using three complementary methods: Pearson, Kendall, and Spearman coefficients. While Pearson's coefficient measures linear relationships, Kendall and Spearman capture monotonic but potentially non-linear relationships between variables [95]. Figure 5 presents heat maps of correlation coefficients that quantify the relationships between UCS and the three experimental parameters.  
All three correlation methods consistently identified cement content as the primary factor influencing UCS, with strong positive correlations (Pearson: 0.87; Kendall: 0.74; Spearman: 0.87). The slightly lower Kendall coefficient suggests some non-linearity in this  
Figure 4: Boxplot of UCS values showing the statistical distribution of measurements. The central box represents the interquartile range (Q1 to Q3), with the horizontal line indicating the median value. Vertical lines (whiskers) extend to show the range of data within 1.5 times the interquartile range. Individual blue dots represent all measured data points, providing visualization of data density and distribution patterns.  
Figure 5: Heat maps of correlation coefficients using three different methods: (**a**) Pearson. (**b**) Kendall. (**c**) Spearman.  
relationship, supporting our observation of accelerating strength gains at higher cement percentages. This finding aligns with established geotechnical engineering principles, which recognize cement dosage as the primary design parameter for soil stabilization projects (e.g., [27; 96; 97; 98]).  
Curing period demonstrated moderate positive correlations with UCS across all methods (Pearson: 0.50; Kendall: 0.45; Spearman: 0.56), reflecting the time-dependent nature of cement hydration and strength development. The higher Spearman coefficient compared to Pearson suggests that the relationship between curing time and UCS may follow a monotonic but not strictly linear pattern. This correlation confirms that while significant strength gains occur during the initial curing period, continued strength enhancement takes place over extended timeframes as cementation processes progress.  
Notably, compaction rate exhibited negligible correlation with UCS across all methods (Pearson: 0.04; Kendall: 0.03; Spearman: 0.03), suggesting that within the range investigated (0.75-1.25 mm/min), variations in compaction velocity have minimal impact on the ultimate strength development of cement-stabilized soil. This finding has important practical implications for field application, indicating that precise control of compaction rate may be less critical than ensuring adequate cement content and sufficient curing time.  
The correlation patterns observed provide valuable guidance for both practical applications and predictive modeling. From an engineering perspective, these results suggest that design efforts should primarily focus on optimizing cement content and ensuring sufficient curing duration, rather than implementing stringent controls on compaction procedures. For modeling purposes, the strong correlation between cement content and UCS, coupled with the moderate correlation with curing period, indicates that these two variables should be prioritized in developing predictive algorithms for strength estimation.