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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Detalhes bibliográficos

Principais autores:	Hao Luo, Ziyu Liu, Song Ge, Linlin Ding, Li Zhang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2025-07-01
coleção:	Applied Sciences
Assuntos:	microseismic event time series multi-scale fusion convolution feature extraction volatility shape similarity algorithm unsupervised clustering
Acesso em linha:	https://www.mdpi.com/2076-3417/15/14/7891
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