Investigation on Intelligent Early Warning of Rock Burst Disasters Using the PCA-PSO-ELM Model

Investigation on Intelligent Early Warning of Rock Burst Disasters Using the PCA-PSO-ELM Model

In order to conduct an intelligent early warning assessment of stope rock burst disasters in mining areas, and effectively prevent and control them, the principal component analysis (PCA) method was embraced to perform dimensionality reduction and feature information extraction from 10 main factors...

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Bibliographic Details
Main Authors: Haiping Yuan, Shuaijie Ji, Gaoliang Liu, Lijun Xiong, Hengzhe Li, Zhanhua Cao, Zijin Xia
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Applied Sciences
Subjects:
rock burst
principal component analysis (PCA) method
particle swarm optimization (PSO) algorithm
extreme learning machine (ELM)
Online Access:https://www.mdpi.com/2076-3417/13/15/8796

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https://www.mdpi.com/2076-3417/13/15/8796

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