Research on the Design of Coal Mine Microseismic Monitoring Network Based on Improved Particle Swarm Optimization
The quality of a mine’s microseismic network layout directly affects the location accuracy of the microseismic network. Introducing the microseismic probability factor <i>F<sub>e</sub></i>, the microseismic importance factor <i>F<sub>Q</sub></i>, and t...
Main Authors: | Kaikai Wang, Chun’an Tang, Ke Ma, Tianhui Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-08-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/17/8439 |
Similar Items
-
An Expert Artificial Intelligence Model for Discriminating Microseismic Events and Mine Blasts
by: Dijun Rao, et al.
Published: (2021-07-01) -
An Enhanced RIME Optimizer with Horizontal and Vertical Crossover for Discriminating Microseismic and Blasting Signals in Deep Mines
by: Wei Zhu, et al.
Published: (2023-10-01) -
Review on Early Warning Methods for Rockbursts in Tunnel Engineering Based on Microseismic Monitoring
by: Shichao Zhang, et al.
Published: (2021-11-01) -
Characteristics of Microseismic Waveforms Induced by Underground Destress Blasting: Comparison With Those Induced by Ground Blasting and Coal Mining
by: Jiliang Kan, et al.
Published: (2022-03-01) -
Discrimination of Microseismic Events in Coal Mine Using Multifractal Method and Moment Tensor Inversion
by: Jiliang Kan, et al.
Published: (2022-06-01)