Optimization-Enhanced Support Vector Machine Algorithms for California Bearing Ratio Prediction of Lateritic Soils: A Comparative Analysis

Key Points

• California Bearing Ratio is effectively predicted using optimization-enhanced support vector machine algorithms, resulting in improved accuracy.
• The study compares various predictive modeling techniques to determine the most effective approach for lateritic soils.
• Results indicate a significant enhancement in prediction accuracy with optimized support vector machine algorithms over traditional methods.
• Findings highlight the importance of advanced modeling techniques in soil engineering, especially for infrastructure applications.