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Evaluating Unsupervised Machine Learning for Seafloor Massive Sulfide Mound Candidates

A TAG hydrothermal field case study using two dimensional spatial data

Machine Learning
Fuzzy Logic
Anomaly Detection
Deep Sea Mining
This thesis evaluates whether two dimensional spatial data can support early exploration screening for seafloor massive sulfide mound candidates at the TAG hydrothermal field.
Author

Fiete Gerhardt

Published

January 1, 2026

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