Tag: Support Vector Machine

Isatis.neo - Sample clustering

Sample clustering in Isatis.neo has proven to be efficient with big datasets
Posted on by Geovariances

Isatis.neo quickly groups borehole samples into homogeneous classes (e.g., facies, geological or mining domains) in an automatic way. Those who have seen the tool run qualifies it as impressive.

Tagged Mining, , , , , , ,





INDUSTRIES:
Mining (13)
Nuclear Decommissioning (7)
Oil & Gas (6)
Hydrogeology (5)
Contaminated sites (5)

TAGS:
Background images (1)
Big data (1)
Conditional simulations (6)
Contaminated sites (2)
Contaminated sites management (2)
Drill hole spacing analysis (2)
Facies modeling (2)
Flow modeling (1)
Geological modeling (3)
H2020 INSIDER (1)
Horizon mapping (1)
Hydrogeological modeling (1)
Ice content evaluation (1)
Isatis (11)
Isatis.neo (15)
Kartotrak (6)
Machine Learning (1)
Mapping (3)
MIK (2)
Mineral resource estimation (6)
Monitoring network optimization (1)
Ore Control (1)
Plurigaussian simulations (1)
Post-accidental situation (2)
Python (1)
Recoverable resource estimation (3)
Resource classification (2)
Resource reporting (1)
Resources workflow (3)
Risk analysis (3)
Sampling clustering (1)
Sampling optimization (3)
Sampling strategy (1)
Scripting procedures (3)
Simulation post-processing (1)
Simulation Reduction (1)
Site characterization (2)
Soil contamination mapping (4)
Spatial Sampling Density Variance (1)
Time-to-Depth conversion (1)
Uncertainty analysis (2)
Uniform Conditioning (5)
Variography (2)
Water quality modeling (1)
Workflow automatization (1)

AUTHORS:

DATES:
2022 (2)
2021 (2)
2020 (2)
2019 (8)
2018 (4)
2017 (3)
2016 (3)