Unsupervised detection of multivariate geochemical anomalies using a high-performance deep autoencoder Gaussian mixture model

It is of great significance to construct an efficient geochemical anomaly detection model for the successful accomplishment of a mineral exploration process in a complex geological environment. However, the complex geological environment of the prospecting area often results in the high-dimensional...

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Veröffentlicht in:	Journal of geochemical exploration Jg. 271; S. 107671
Hauptverfasser:	Wang, Xuemei, Chen, Yongliang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2025
Schlagworte:	Deep autoencoder Deep autoencoder Gaussian mixture model Gaussian mixture model Geochemical exploration data Mineral exploration Multivariate anomaly detection Multivariate anomaly detection Deep autoencoder Gaussian mixture model Mineral exploration Gaussian mixture model Geochemical exploration data Deep autoencoder
ISSN:	0375-6742
Online-Zugang:	Volltext
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