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What is Predicting UCS from Point Load Strength about?

This study investigates the use of point load tests to predict the Unconfined Compressive Strength (UCS) of various rock types from Chennai and Bangalore, utilizing five machine learning models for improved accuracy. The results indicate that the Neural Network and Gaussian Process Regression models outperformed others, demonstrating a strong correlation between point load index and UCS, particularly with axial tests yielding an R² of 0.996. The findings suggest that point load tests can effectively estimat

Author

semester2gh

Language

EN