Abstract

This study aims to evaluate the feasibility and effectiveness of a modified adaptive genetic algorithm (AGA) with Universal Distinct Element Code (UDEC) simulation in analyzing fracture surface feature points of an anticline rocky slope. Using coordinate data from 30 fracture surface feature points, the traditional GA and modified AGA methods were compared, with the mean value of the normalized Mahalanobis distance indicating the reliability of the results. The study found that the modified AGA approach with UDEC had a significantly smaller mean value of normalized Mahalanobis distance than the traditional GA approach, demonstrating its higher accuracy and reliability in analyzing the fracture surface feature points of the rocky slope. Additionally, the research found that the location of the fracture surface of the anticline rocky slope is closely related to the inhomogeneous bulk density caused by weathering. These findings contribute to sustainability efforts by improving our understanding of the behavior of rocky slopes, informing better land management and infrastructure planning, and reducing uncertainties in predicting the behavior of rocky slopes for more sustainable infrastructure development and land management practices.

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