An Algorithm for the Shape-Based Distance of Microseismic Time Series Waveforms and Its Application in Clustering Mining Events

An Algorithm for the Shape-Based Distance of Microseismic Time Series Waveforms and Its Application in Clustering Mining Events

To improve the efficiency and accuracy of microseismic event extraction from time-series data and enhance the detection of anomalous events, this paper proposes a Multi-scale Fusion Convolution and Dilated Convolution Autoencoder (MDCAE) combined with a Constraint Shape-Based Distance algorithm inco...

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Bibliographic Details
Main Authors: Hao Luo, Ziyu Liu, Song Ge, Linlin Ding, Li Zhang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
microseismic event time series
multi-scale fusion convolution
feature extraction
volatility
shape similarity algorithm
unsupervised clustering
Online Access:https://www.mdpi.com/2076-3417/15/14/7891
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