Evaluation of Short-Term Rockburst Risk Severity Using Machine Learning Methods

Evaluation of Short-Term Rockburst Risk Severity Using Machine Learning Methods

In deep engineering, rockburst hazards frequently result in injuries, fatalities, and the destruction of contiguous structures. Due to the complex nature of rockbursts, predicting the severity of rockburst damage (intensity) without the aid of computer models is challenging. Although there are vario...

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Bibliographic Details
Main Authors: Aibing Jin, Prabhat Basnet, Shakil Mahtab
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Big Data and Cognitive Computing
Subjects:
short-term rockburst
risk prediction
principal component analysis
categorical gradient boosting
class imbalance
hazard risk modelling
Online Access:https://www.mdpi.com/2504-2289/7/4/172

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