Published June 17, 2021
| Version v3
Dataset
Open
An Improved Tandem Neural Network Architecture for Inverse Modeling of Multicomponent Reactive Transport in Porous Media
Authors/Creators
- 1. Jilin University
- 2. Nanjing University
- 3. University of Cincinnati
Description
This data includes the training and testing dataset for DNN design and the observation data of synthetic example for validation.
The code of TNNA-AUS inversion method.
Files
Description of the dataset.pdf
Files
(30.0 MB)
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