Enhancing unconfined compressive strength of stabilized soil with lime and cement prediction through a robust hybrid machine learning approach utilizing Naive Bayes Algorithm

Enhancing unconfined compressive strength of stabilized soil with lime and cement prediction through a robust hybrid machine learning approach utilizing Naive Bayes Algorithm

Abstract The unconfined compressive strength (UCS) of stabilized soil with lime and cement is a crucial mechanical factor in developing accurate geomechanical models. In the past, determining UCS required laborious laboratory testing of core samples or complex well-log analysis, both of which consum...

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Bibliographic Details
Main Author: Weiqing Wan
Format: Article
Language:English
Published: SpringerOpen 2024-04-01
Series:Journal of Engineering and Applied Science
Subjects:
Unconfined compressive strength
Machine learning
Naive Bayes
Smell agent optimization
Dynamic arithmetic optimization algorithm
Online Access:https://doi.org/10.1186/s44147-024-00408-8

Internet

https://doi.org/10.1186/s44147-024-00408-8

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