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DOI: 10.4121/3d08ee40-04f3-4b8f-94c1-018090ad2a09

Wang, Liang; Heimovaara, Timo (2025): Data and scripts underlying the manuscript: Quantifying water content of a landfill with ERT data by Bayesian evidential learning. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/3d08ee40-04f3-4b8f-94c1-018090ad2a09.v1

Categories

• Environmental Science and Management
• Geophysics
• Earth Sciences
• Environmental Sciences

Keywords

Bayesian evidential learning ERT hydrogeophysics water content

Licence

MIT

Interoperability

• RO-Crate Metadata

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by Liang Wang , Timo Heimovaara

This file includes the scripts and data used in the manuscript: Quantifying water content of a landfill with ERT data by Bayesian evidential learning. The raw data are 4 ERT measurement datasets. We want to estimate the total water content of the subsurface based on these measurement data. The Python scripts included are used to implement the Bayesian evidential learning algorithm and make predictions. The users can use a1_XX.py to generate samples, use a2_XXX to perform the falsification, and use b_bnn to run the regression.

History

• 2025-06-02 first online, published, posted

Publisher

4TU.ResearchData

Format

python scripts, .dat files(geophysical measurement data)

Funding

• Coupled mUlti-process research for reducing landfill emissions (CURE) (grant code OCENW.GROOT.2O19.O92) [more info...] Dutch National Science Foundation (NWO)

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Engineering