Developing rock mass classification method using precise description of joints

Article Energy & Fuels

Rock mass classification method applying neural networks to minimize geomechanical characterization in underground Peruvian mines

Julyans Brousset et al.

Summary: This research utilizes artificial neural networks to improve the classification of rock mass in underground mining, providing a more accurate and reliable solution by adapting to geological changes and delivering precise classification results.

ENERGY REPORTS (2023)

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Article Engineering, Geological

Real-time prediction of rock mass classification based on TBM operation big data and stacking technique of ensemble learning

Shaokang Hou et al.

Summary: This study proposes a stacking ensemble classifier for the real-time prediction of rock mass classification using TBM operation data. The results show that the stacking ensemble classifier outperforms individual classifiers, demonstrating strong learning and generalization abilities for small and imbalanced samples.

JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING (2022)

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Article Acoustics

Fuzzy Clustering Analysis of HVSR Data for Seismic Microzonation at Lahore City

Sarfraz Khan et al.

Summary: This paper presents the results of a microzonation study in Lahore, Pakistan, which analyzes the resonance frequency and peak amplitude in different areas of the city. The study provides valuable information on soil and geological characteristics, and can be used to reduce seismic risk for infrastructure in Lahore.

SHOCK AND VIBRATION (2022)

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Article Mathematics, Interdisciplinary Applications