# Prediction of Unconfined Compressive Strength in Cement-Treated Soils: A Machine Learning Approach
## 3 Results and Discussion
### Uncertainty Quantification System Performance
#### 3.3.4 Practical Application Examples  
Having established both the technical reliability and interpretability of the system, practical application scenarios demonstrate how uncertainty quantification enhances engineering decision-making in real-world contexts. The following examples utilize actual predictions from the deployed system, showcasing its capability to provide actionable information that supports both preliminary design and construction quality control in real geotechnical projects. For an application with moderate strength requirements (UCS \(\leq\) 2000 kPa), one may consider a soil treated with 5% cement, compacted at 1.0 mm/min and cured for 14 days. In this scenario, the uncertainty quantification system predicts a central UCS value of 2344 kPa with an uncertainty estimate of 242 kPa, resulting in a 95% confidence interval of [1870 kPa, 2818 kPa]. The interval width of 948 kPa represents a relative uncertainty of \(\pm\)20.2%, providing the geotechnical engineer with both the expected strength and a quantified range of probable outcomes essential for informed decision-making about safety factors and design margins. The SHAP waterfall analysis for this scenario (Figure 13) reveals the mechanistic contributions underlying the prediction. Starting from the baseline expectation of 2180 kPa across all experimental conditions, the 14-day curing period contributes the largest positive impact of +308 kPa, reflecting the substantial strength development achieved through cement hydration during the first two weeks. The 5% cement content contributes \(-\)158 kPa relative to baseline, indicating that this moderate dosage falls below the experimental average and thus reduces strength expectations accordingly. The compaction rate contributesa minimal +14 kPa, confirming its limited practical significance in strength development. This decomposition enables engineers to understand precisely which parameters drive the predicted outcome and how modifications might affect results. The practical value of this uncertainty information becomes immediately evident when evaluating design alternatives. If the project requires a minimum UCS of 1800 kPa, the engineer can proceed confidently with the 5% cement design, knowing that even the lower bound of the confidence interval (1870 kPa) exceeds the requirement with a margin. However, if the minimum requirement were 2500 kPa, the uncertainty information reveals that while the central prediction approaches the target, there exists a meaningful probability of falling short, suggesting the need for either increased cement content or extended curing time to ensure reliable performance. For more demanding applications requiring substantial strength levels, one may consider a soil treated with 10% cement, compacted at 1.0 mm/min and cured for 28 days. In this scenario, the system predicts a central UCS value of 4258 kPa with an uncertainty estimate of 293 kPa, which yields a 95% confidence interval of [3683 kPa, 4833 kPa]. The interval width of 1150 kPa represents a relative uncertainty of \(\pm\)13.5%, notably lower than the moderate strength scenario despite the larger absolute uncertainty magnitude. This enhanced predictability accompanies higher degrees of stabilization and supports more aggressive design optimization for projects where material costs represent significant considerations. The SHAP analysis for this high-strength scenario (Figure 14) demonstrates dramatically different contribution patterns compared to the moderate strength case. Starting from the same baseline of 2180 kPa, the 10% cement content delivers a massive positive contribution of +1411 kPa, representing the dominant factor in achieving high strength levels. The extended 28 day curing period adds a substantial +685 kPa, reflecting continued hydration reactions that become increasingly valuable at higher cement contents. The compaction rate again shows minimal influence, confirming its limited practical significance across the entire strength spectrum.