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Clustering analysis of a solid waste landfill using ERT and TDIP geophysical data
K
H
X
R
J
DOI:10.1016/j.wasman.2026.115731.png)
Abstract
En 中文
• ML-enhanced geophysics autonomously identifies landfill waste contamination zones. • K-means clustering of resistivity and phase performs waste type and spatial zoning. • Unsupervised clustering reduces interpretation bias in landfill characterization.
Keywords:
Induced polarization (IP)
K-means clustering
Solid waste deposits
Chromium-containing sludge
Borehole validation
Journal
IF:
7.1
Papers:
10.0K
Citations:
5.3W
Organization
No organization information available
