Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm
This paper introduces a novel methodology for predicting Unconfined Compressive Strength (UCS) in rocks by integrating Support Vector Regression (SVR) with two cutting-edge optimization algorithms: the Seahorse Optimizer (SO) and the COOT Optimization Algorithm (COOT). Unlike traditional UCS predict...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Bilijipub publisher
2024-12-01
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| Series: | Advances in Engineering and Intelligence Systems |
| Subjects: | |
| Online Access: | https://aeis.bilijipub.com/article_212432_e4c2aee397acd0798ae9f8644aea0610.pdf |
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